| Author | Title | Year | Journal/Proceedings | Reftype | DOI/URL |
|---|---|---|---|---|---|
| Soliman, A., Al-Ali, A., Mohamed, A., Gedawy, H., Izham, D., Bahri, M., Erbad, A. and Guizani, M. | AI-based UAV navigation framework with digital twin technology for mobile target visitation [BibTeX] |
2023 | Engineering Applications of Artificial Intelligence Vol. 123, pp. 106318 |
article | DOI |
BibTeX:
@article{Soliman_2023,
author = {Abdulrahman Soliman and Abdulla Al-Ali and Amr Mohamed and Hend Gedawy and Daniel Izham and Mohamad Bahri and Aiman Erbad and Mohsen Guizani},
title = {AI-based UAV navigation framework with digital twin technology for mobile target visitation},
journal = {Engineering Applications of Artificial Intelligence},
publisher = {Elsevier BV},
year = {2023},
volume = {123},
pages = {106318},
doi = {https://doi.org/10.1016/j.engappai.2023.106318}
}
|
|||||
| Abdaoui, A., Erbad, A., Al-Ali, A., Mohamed, A. and Guizani, M. | Fuzzy Elliptic Curve Cryptography for Authentication in Internet of Things | 2022 | IEEE Internet of Things Journal Vol. 9 |
article | DOI |
| Abstract: The security and privacy of the network in Internet of Things (IoT) systems are becoming more critical as we are more dependent on smart systems. Considering that packets are exchanged between the end user and the sensing devices, it is then important to ensure the security, privacy, and integrity of the transmitted data by designing a secure and a lightweight authentication protocol for IoT systems. In this article, in order to improve the authentication and the encryption in IoT systems, we present a novel method of authentication and encryption based on elliptic curve cryptography (ECC) using random numbers generated by fuzzy logic. We evaluate our novel key generation method by using standard randomness tests, such as: frequency test, frequency test with mono block, run test, discrete Fourier transform (DFT) test, and advanced DFT test. Our results show superior performance compared to existing ECC based on shift registers. In addition, we apply some attack algorithms, such as Pollard's ρ and Baby-step Giant-step, to evaluate the vulnerability of the proposed scheme. | |||||
BibTeX:
@article{Abdaoui2022,
author = {A. Abdaoui and A. Erbad and A.K. Al-Ali and A. Mohamed and M. Guizani},
title = {Fuzzy Elliptic Curve Cryptography for Authentication in Internet of Things},
journal = {IEEE Internet of Things Journal},
year = {2022},
volume = {9},
doi = {https://doi.org/10.1109/JIOT.2021.3121350}
}
|
|||||
| Aggarwal, M., Zubair, M., Unal, D., Al-Ali, A., Reimann, T. and Alinier, G. | Fuzzy Identification-Based Encryption for healthcare user face authentication [BibTeX] |
2022 | Journal of Emergency Medicine, Trauma and Acute Care Vol. 2022 |
article | DOI |
BibTeX:
@article{Aggarwal2022,
author = {Mahima Aggarwal and Mohammed Zubair and Devrim Unal and Abdulla Al-Ali and Thomas Reimann and Guillaume Alinier},
title = {Fuzzy Identification-Based Encryption for healthcare user face authentication},
journal = {Journal of Emergency Medicine, Trauma and Acute Care},
year = {2022},
volume = {2022},
doi = {https://doi.org/10.5339/jemtac.2022.qhc.72}
}
|
|||||
| Chamkhia, H., Erbad, A., Al-Ali, A., Mohamed, A., Refaey, A. and Guizani, M. | 3-D Stochastic Geometry-Based Modeling and Performance Analysis of Efficient Security Enhancement Scheme for IoT Systems | 2022 | IEEE Internet of Things Journal Vol. 9 |
article | DOI |
| Abstract: Internet of Things (IoT) systems are becoming core building blocks for different services and applications supporting every day's life. The heterogeneous nature of IoT devices and the complex use scenarios make it hard to build secure and private IoT systems. Physical-layer security (PLS) can lead to efficient solutions reducing the impact of the increasing security threats. In this work, we propose a new PLS-based IoT transmission scheme that offers a highly secured transmission probability, low-computational complexity, and reduced power consumption. We utilize 3-D stochastic geometry to model a more realistic IoT system and test our proposed scheme in different practical scenarios, where sensors, access points (APs), and eavesdroppers are randomly located in 3-D space. We focus on the system performance, in terms of secrecy outage probability (SOP) and secured successful transmission probability (SSTP), using tight closed-form expressions. An optimization problem is developed to deduce the optimal sensors' transmit power, the APs' density, and the maximum number of transmission tentative, when maximizing the SSTP. The proposed scheme outperforms the baseline retransmission scheme, in terms of SOP and SSTP based on analytical and simulation results. | |||||
BibTeX:
@article{Chamkhia2022,
author = {H. Chamkhia and A. Erbad and A.K. Al-Ali and A. Mohamed and A. Refaey and M. Guizani},
title = {3-D Stochastic Geometry-Based Modeling and Performance Analysis of Efficient Security Enhancement Scheme for IoT Systems},
journal = {IEEE Internet of Things Journal},
year = {2022},
volume = {9},
doi = {https://doi.org/10.1109/JIOT.2021.3112883}
}
|
|||||
| Gupta, L., Salman, T., Ghubaish, A., Unal, D., Al-Ali, A. and Jain, R. | Cybersecurity of multi-cloud healthcare systems: A hierarchical deep learning approach | 2022 | Applied Soft Computing Vol. 118 |
article | DOI |
| Abstract: With the increase in sophistication and connectedness of the healthcare networks, their attack surfaces and vulnerabilities increase significantly. Malicious agents threaten patients’ health and life by stealing or altering data as it flows among the multiple domains of healthcare networks. The problem is likely to exacerbate with the increasing use of IoT devices, edge, and core clouds in the next generation healthcare networks. Presented in this paper is MUSE, a system of deep hierarchical stacked neural networks for timely and accurate detection of malicious activity that leads to alteration of meta-information or payload of the dataflow between the IoT gateway, edge and core clouds. Smaller models at the edge clouds take substantially less time to train as compared to the large models in the core cloud. To improve the speed of training and accuracy of detection of large core cloud models, the MUSE system uses a novel method of merging and aggregating layers of trained edge cloud models to construct a partly pre-trained core cloud model. As a result, the model in the core cloud takes substantially smaller number of epochs (6 to 8) and, consequently, less time, compared to those in the edge clouds, training of which take 35 to 40 epochs to converge. With the help of extensive evaluations, it is shown that with the MUSE system, large, merged models can be trained in significantly less time than the unmerged models that are created independently in the core cloud. Through several runs it is seen that the merged models give on an average 26.2% reduction in training times. From the experimental evaluation we demonstrate that along with fast training speeds the merged MUSE model gives high training and test accuracies, ranging from 95% to 100%, in detection of unknown attacks on dataflows. The merged model thus generalizes very well on the test data. This is a marked improvement when compared with the accuracy given by un-merged model as well as accuracy reported by other researchers with newer datasets. | |||||
BibTeX:
@article{Gupta2022,
author = {L. Gupta and T. Salman and A. Ghubaish and D. Unal and A.K. Al-Ali and R. Jain},
title = {Cybersecurity of multi-cloud healthcare systems: A hierarchical deep learning approach},
journal = {Applied Soft Computing},
year = {2022},
volume = {118},
doi = {https://doi.org/10.1016/j.asoc.2022.108439}
}
|
|||||
| Jouhari, M., Al-Ali, A., Baccour, E., Mohamed, A., Erbad, A., Guizani, M. and Hamdi, M. | Distributed CNN Inference on Resource-Constrained UAVs for Surveillance Systems: Design and Optimization | 2022 | IEEE Internet of Things Journal Vol. 9 |
article | DOI |
| Abstract: Unmanned aerial vehicles (UAVs) have attracted great interest in the last few years owing to their ability to cover large areas and access difficult and hazardous target zones, which is not the case of traditional systems relying on direct observations obtained from fixed cameras and sensors. Furthermore, thanks to the advancements in computer vision and machine learning, UAVs are being adopted for a broad range of solutions and applications. However, deep neural networks (DNNs) are progressing toward deeper and complex models that prevent them from being executed onboard. In this article, we propose a DNN distribution methodology within UAVs to enable data classification in resource-constrained devices and avoid extra delays introduced by the server-based solutions due to data communication over air-to-ground links. The proposed method is formulated as an optimization problem that aims to minimize the latency between data collection and decision-making while considering the mobility model and the resource constraints of the UAVs as part of the air-to-air communication. We also introduce the mobility prediction to adapt our system to the dynamics of UAVs and the network variation. The simulation conducted to evaluate the performance and benchmark the proposed methods, namely, optimal UAV-based layer distribution (OULD) and OULD with mobility prediction (OULD-MP), was run in an HPC cluster. The obtained results show that our optimization solution outperforms the existing and heuristic-based approaches. | |||||
BibTeX:
@article{Jouhari2022,
author = {M. Jouhari and A.K. Al-Ali and E. Baccour and A. Mohamed and A. Erbad and M. Guizani and M. Hamdi},
title = {Distributed CNN Inference on Resource-Constrained UAVs for Surveillance Systems: Design and Optimization},
journal = {IEEE Internet of Things Journal},
year = {2022},
volume = {9},
doi = {https://doi.org/10.1109/JIOT.2021.3079164}
}
|
|||||
| Zubair, M., Ghubaish, A., Unal, D., Al-Ali, A., Reimann, T., Alinier, G., Hammoudeh, M. and Qadir, J. | Secure Bluetooth Communication in Smart Healthcare Systems: A Novel Community Dataset and Intrusion Detection System † | 2022 | Sensors Vol. 22 |
article | DOI |
| Abstract: Smart health presents an ever-expanding attack surface due to the continuous adoption of a broad variety of Internet of Medical Things (IoMT) devices and applications. IoMT is a common approach to smart city solutions that deliver long-term benefits to critical infrastructures, such as smart healthcare. Many of the IoMT devices in smart cities use Bluetooth technology for short-range communication due to its flexibility, low resource consumption, and flexibility. As smart healthcare applications rely on distributed control optimization, artificial intelligence (AI) and deep learning (DL) offer effective approaches to mitigate cyber-attacks. This paper presents a decentralized, predictive, DL-based process to autonomously detect and block malicious traffic and provide an end-to-end defense against network attacks in IoMT devices. Furthermore, we provide the BlueTack dataset for Bluetooth-based attacks against IoMT networks. To the best of our knowledge, this is the first intrusion detection dataset for Bluetooth classic and Bluetooth low energy (BLE). Using the BlueTack dataset, we devised a multi-layer intrusion detection method that uses deep-learning techniques. We propose a decentralized architecture for deploying this intrusion detection system on the edge nodes of a smart healthcare system that may be deployed in a smart city. The presented multi-layer intrusion detection models achieve performances in the range of 97–99.5% based on the F1 scores. | |||||
BibTeX:
@article{Zubair2022,
author = {M. Zubair and A. Ghubaish and D. Unal and A. Al-Ali and T. Reimann and G. Alinier and M. Hammoudeh and J. Qadir},
title = {Secure Bluetooth Communication in Smart Healthcare Systems: A Novel Community Dataset and Intrusion Detection System †},
journal = {Sensors},
year = {2022},
volume = {22},
doi = {https://doi.org/10.3390/s22218280}
}
|
|||||
| Al-Emadi, S., Al-Ali, A. and Al-Ali, A. | Audio-based drone detection and identification using deep learning techniques with dataset enhancement through generative adversarial networks† | 2021 | Sensors Vol. 21 |
article | DOI |
| Abstract: Drones are becoming increasingly popular not only for recreational purposes but in day-to-day applications in engineering, medicine, logistics, security and others. In addition to their useful applications, an alarming concern in regard to the physical infrastructure security, safety and privacy has arisen due to the potential of their use in malicious activities. To address this problem, we propose a novel solution that automates the drone detection and identification processes using a drone’s acoustic features with different deep learning algorithms. However, the lack of acoustic drone datasets hinders the ability to implement an effective solution. In this paper, we aim to fill this gap by introducing a hybrid drone acoustic dataset composed of recorded drone audio clips and artificially generated drone audio samples using a state-of-the-art deep learning technique known as the Generative Adversarial Network. Furthermore, we examine the effectiveness of using drone audio with different deep learning algorithms, namely, the Convolutional Neural Network, the Recurrent Neural Network and the Convolutional Recurrent Neural Network in drone detection and identification. Moreover, we investigate the impact of our proposed hybrid dataset in drone detection. Our findings prove the advantage of using deep learning techniques for drone detection and identification while confirming our hypothesis on the benefits of using the Generative Adversarial Networks to generate real-like drone audio clips with an aim of enhancing the detection of new and unfamiliar drones. | |||||
BibTeX:
@article{,
author = {S. Al-Emadi and A. Al-Ali and A. Al-Ali},
title = {Audio-based drone detection and identification using deep learning techniques with dataset enhancement through generative adversarial networks†},
journal = {Sensors},
year = {2021},
volume = {21},
doi = {https://doi.org/10.3390/s21154953}
}
|
|||||
| Ghubaish, A., Salman, T., Zolanvari, M., Unal, D., Al-Ali, A. and Jain, R. | Recent Advances in the Internet-of-Medical-Things (IoMT) Systems Security | 2021 | IEEE Internet of Things Journal Vol. 8 |
article | DOI |
| Abstract: The rapid evolutions in microcomputing, mini-hardware manufacturing, and machine-to-machine (M2M) communications have enabled novel Internet-of-Things (IoT) solutions to reshape many networking applications. Healthcare systems are among these applications that have been revolutionized with IoT, introducing an IoT branch known as the Internet-of-Medical Things (IoMT) systems. IoMT systems allow remote monitoring of patients with chronic diseases. Thus, it can provide timely patients' diagnostic that can save their life in case of emergencies. However, security in these critical systems is a major challenge facing their wide utilization. In this article, we present state-of-the-art techniques to secure IoMT systems' data during collection, transmission, and storage. We comprehensively overview IoMT systems' potential attacks, including physical and network attacks. Our findings reveal that most security techniques do not consider various types of attacks. Hence, we propose a security framework that combines several security techniques. The framework covers IoMT security requirements and can mitigate most of its known attacks. | |||||
BibTeX:
@article{Ghubaish2021,
author = {A. Ghubaish and T. Salman and M. Zolanvari and D. Unal and A. Al-Ali and R. Jain},
title = {Recent Advances in the Internet-of-Medical-Things (IoMT) Systems Security},
journal = {IEEE Internet of Things Journal},
year = {2021},
volume = {8},
doi = {https://doi.org/10.1109/JIOT.2020.3045653}
}
|
|||||
| Hussain, S., Fernandez, J.H., Al-Ali, A. and Shikfa, A. | Vulnerabilities and countermeasures in electrical substations | 2021 | International Journal of Critical Infrastructure Protection Vol. 33 |
article | DOI |
| Abstract: The impending and continued threat of cyberattacks on modern utility grids has called for action from the different stakeholders of the electricity sector. This calls for a thorough investigation and review of the weaknesses present in the distribution substations – the backbone of the grid – that can attract attackers to achieve their malicious objectives. The present survey deals with this issue and identifies both the common and specific vulnerabilities present in substations that can be exploited by potential attackers. This work approaches the topic, for the first time, from an attacker's perspective, in order to categorize the possible attack vectors that could be used to first access the substation network, and then disrupt the substation operations under the purview of IEC standards. The reported literature in the field was critically analyzed from an attacker's perspective to highlight the potential threats that can become a liability in cyberattacks on substations. Countermeasures pertaining to these cyberattacks are then detailed and the main elements required for a comprehensive electrical substation cybersecurity solution are finally outlined. | |||||
BibTeX:
@article{Hussain2021,
author = {S. Hussain and J. Hernandez Fernandez and A.K. Al-Ali and A. Shikfa},
title = {Vulnerabilities and countermeasures in electrical substations},
journal = {International Journal of Critical Infrastructure Protection},
year = {2021},
volume = {33},
doi = {https://doi.org/10.1016/j.ijcip.2020.100406}
}
|
|||||
| Unal, D., Al-Ali, A., Catak, F. and Hammoudeh, M. | A secure and efficient Internet of Things cloud encryption scheme with forensics investigation compatibility based on identity-based encryption | 2021 | Future Generation Computer Systems Vol. 125 |
article | DOI |
| Abstract: Data security is a challenge for end-users of cloud services as the users have no control over their data once it is transmitted to the cloud. A potentially corrupt cloud service provider can obtain the end-users’ data. Conventional PKI-based solutions are insufficient for large-scale cloud systems, considering efficiency, scalability, and security. In large-scale cloud systems, the key management requirements include scalable encryption, authentication, and non-repudiation services, as well as the ability to share files with different users and data recovery when the user keys of encrypted data are not accessible. Further requirements in cloud systems include the ability to provide the means for digital forensic investigations on encrypted data. Once data on the cloud is encrypted with a user's key it becomes impossible to access by forensic investigation teams. In this regard, distributing the trust of key management into multiple authorities is desirable. In the literature, there is no available secure cloud storage system with secure and efficient Type-3 pairings, supporting Encryption-as-a-Service (EaaS) and multiple Public Key Generators (PKGs). This paper proposes an efficient Identity-based cryptography (IBC) architecture for secure cloud storage, named Secure Cloud Storage System (SCSS), which supports distributed key management and encryption mechanisms and support for multiple PKGs. During forensic investigations, the legal authorities will be able to use the multiple PKG mechanism for data access, while an account locking mechanism prevents a single authority to access user data due to trust distribution. We also demonstrate that, the IBC scheme used in SCSS has better performance compared to similar schemes in the literature. For the security levels of 128-bits and above, SCSS has better scalability compared to existing schemes, with respect to encryption and decryption operations. Since the decryption operation is frequently needed for forensic analysis, the improved scalability results in a streamlined forensic investigation process on the encrypted data in the cloud. | |||||
BibTeX:
@article{Unal2021,
author = {D. Unal and A. Al-Ali and F.O. Catak and M. Hammoudeh},
title = {A secure and efficient Internet of Things cloud encryption scheme with forensics investigation compatibility based on identity-based encryption},
journal = {Future Generation Computer Systems},
year = {2021},
volume = {125},
doi = {https://doi.org/10.1016/j.future.2021.06.050}
}
|
|||||
| Al-Garadi, M., Mohamed, A., Al-Ali, A., Du, X., Ali, I. and Guizani, M. | A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security | 2020 | IEEE Communications Surveys and Tutorials Vol. 22 |
article | DOI |
| Abstract: The Internet of Things (IoT) integrates billions of smart devices that can communicate with one another with minimal human intervention. IoT is one of the fastest developing fields in the history of computing, with an estimated 50 billion devices by the end of 2020. However, the crosscutting nature of IoT systems and the multidisciplinary components involved in the deployment of such systems have introduced new security challenges. Implementing security measures, such as encryption, authentication, access control, network and application security for IoT devices and their inherent vulnerabilities is ineffective. Therefore, existing security methods should be enhanced to effectively secure the IoT ecosystem. Machine learning and deep learning (ML/DL) have advanced considerably over the last few years, and machine intelligence has transitioned from laboratory novelty to practical machinery in several important applications. Consequently, ML/DL methods are important in transforming the security of IoT systems from merely facilitating secure communication between devices to security-based intelligence systems. The goal of this work is to provide a comprehensive survey of ML methods and recent advances in DL methods that can be used to develop enhanced security methods for IoT systems. IoT security threats that are related to inherent or newly introduced threats are presented, and various potential IoT system attack surfaces and the possible threats related to each surface are discussed. We then thoroughly review ML/DL methods for IoT security and present the opportunities, advantages and shortcomings of each method. We discuss the opportunities and challenges involved in applying ML/DL to IoT security. These opportunities and challenges can serve as potential future research directions. | |||||
BibTeX:
@article{,
author = {M.A. Al-Garadi and A. Mohamed and A.K. Al-Ali and X. Du and I. Ali and M. Guizani},
title = {A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security},
journal = {IEEE Communications Surveys and Tutorials},
year = {2020},
volume = {22},
doi = {https://doi.org/10.1109/COMST.2020.2988293}
}
|
|||||
| Kunhoth, J., Karkar, A., Al-Maadeed, S. and Al-Ali, A. | Indoor positioning and wayfinding systems: a survey | 2020 | Human-centric Computing and Information Sciences Vol. 10 |
article | DOI |
| Abstract: Navigation systems help users access unfamiliar environments. Current technological advancements enable users to encapsulate these systems in handheld devices, which effectively increases the popularity of navigation systems and the number of users. In indoor environments, lack of Global Positioning System (GPS) signals and line of sight with orbiting satellites makes navigation more challenging compared to outdoor environments. Radio frequency (RF) signals, computer vision, and sensor-based solutions are more suitable for tracking the users in indoor environments. This article provides a comprehensive summary of evolution in indoor navigation and indoor positioning technologies. In particular, the paper reviews different computer vision-based indoor navigation and positioning systems along with indoor scene recognition methods that can aid the indoor navigation. Navigation and positioning systems that utilize pedestrian dead reckoning (PDR) methods and various communication technologies, such as Wi-Fi, Radio Frequency Identification (RFID) visible light, Bluetooth and ultra-wide band (UWB), are detailed as well. Moreover, this article investigates and contrasts the different navigation systems in each category. Various evaluation criteria for indoor navigation systems are proposed in this work. The article concludes with a brief insight into future directions in indoor positioning and navigation systems. | |||||
BibTeX:
@article{Kunhoth2020,
author = {J. Kunhoth and A.G. Karkar and S. Al-Maadeed and A. Al-Ali},
title = {Indoor positioning and wayfinding systems: a survey},
journal = {Human-centric Computing and Information Sciences},
year = {2020},
volume = {10},
doi = {https://doi.org/10.1186/s13673-020-00222-0}
}
|
|||||
| Naji, K., Du, X., Tarlochan, F., Ebead, U., Hasan, M. and Al-Ali, A. | Engineering students' readiness to transition to emergency online learning in response to COVID-19: Case of Qatar | 2020 | Eurasia Journal of Mathematics, Science and Technology Education Vol. 16 |
article | DOI |
| Abstract: This study examined engineering students' initial readiness to transition to emergency online learning in response to COVID-19 in Qatar. A theoretical framework is proposed for understanding the factors influencing students' readiness for change. Sequential explanatory mixed-method research was conducted, with 140 participants completing an online survey, of which 68 also contributed written reflections and 8 participated in semi-structured interviews. Exploratory factor analysis displayed a four-factor structure, including initial preparedness and motivation for online learning, self-efficacy beliefs about online learning, self-directed learning online, and support. The qualitative outcomes supported the four factors and provided further insight into their varied and nuanced manifestation. In accounting for the perceived impact of the factors on readiness, significant differences were identified regarding pedagogical mode, with students enrolled in PBL courses reporting higher readiness than those from non-PBL courses. The practical implications for preparing students for future emergency online learning are discussed. | |||||
BibTeX:
@article{Naji2020,
author = {K.K. Naji and X. Du and F. Tarlochan and U. Ebead and M.A. Hasan and A.K. Al-Ali},
title = {Engineering students' readiness to transition to emergency online learning in response to COVID-19: Case of Qatar},
journal = {Eurasia Journal of Mathematics, Science and Technology Education},
year = {2020},
volume = {16},
doi = {https://doi.org/10.29333/EJMSTE/8474}
}
|
|||||
| Naji, K., Ebead, U., Al-Ali, A. and Du, X. | Comparing models of problem and project-based learning (PBL) courses and student engagement in civil engineering in Qatar | 2020 | Eurasia Journal of Mathematics, Science and Technology Education Vol. 16 |
article | DOI |
| Abstract: Background: While improved student engagement has been highlighted as an essential goal and a major outcome of Problem and Project-Based learning (PBL), little empirical evidence has been provided regarding types and forms of student engagement. Material and method: The study explored forms of student engagement in PBL settings, drawing on empirical data of observations and group interviews with 23 project teams (116 students) in four different PBL undergraduate civil engineering courses at Qatar University. Results: The study identified four patterns of student engagement in a PBL setting. Participants reported significant indicators of the first two patterns-engagement as autonomy and as connection. Regarding the other two indicators, namely relational and emotional engagement, they reported positive yet slightly fewer indicators. Three factors were identified that influenced student engagement in a project teams, namely PBL types and its appropriateness to the nature of the course, students' prior experiences with PBL, and team dynamics. Conclusions: These results facilitate the establishment of an institutional framework supporting a progressive approach to embracing PBL. In this framework PBL implementation begins with diverse practices at the course level and has systemic change as its ultimate goal. This framework particularly aims to support an institutionalized approach to transition to PBL in a socio-cultural context (e.g., a non-western context) where instructors are as the primary and authoritative source of knowledge. The overall outcome of the study supports management of change from a lecture-based mode to PBL in a non-western context. | |||||
BibTeX:
@article{Naji2020,
author = {K.K. Naji and U. Ebead and A.K. Al-Ali and X. Du},
title = {Comparing models of problem and project-based learning (PBL) courses and student engagement in civil engineering in Qatar},
journal = {Eurasia Journal of Mathematics, Science and Technology Education},
year = {2020},
volume = {16},
doi = {https://doi.org/10.29333/EJMSTE/8291}
}
|
|||||
| Rathore, H., Fu, C., Mohamed, A., Al-Ali, A., Du, X., Guizani, M. and Yu, Z. | Multi-layer security scheme for implantable medical devices | 2020 | Neural Computing and Applications Vol. 32 |
article | DOI |
| Abstract: Internet of Medical Things (IoMTs) is fast emerging, thereby fostering rapid advances in the areas of sensing, actuation and connectivity to significantly improve the quality and accessibility of health care for everyone. Implantable medical device (IMD) is an example of such an IoMT-enabled device. IMDs treat the patient’s health and give a mechanism to provide regular remote monitoring to the healthcare providers. However, the current wireless communication channels can curb the security and privacy of these devices by allowing an attacker to interfere with both the data and communication. The privacy and security breaches in IMDs have thereby alarmed both the health providers and government agencies. Ensuring security of these small devices is a vital task to prevent severe health consequences to the bearer. The attacks can range from system to infrastructure levels where both the software and hardware of the IMD are compromised. In the recent years, biometric and cryptographic approaches to authentication, machine learning approaches to anomaly detection and external wearable devices for wireless communication protection have been proposed. However, the existing solutions for wireless medical devices are either heavy for memory constrained devices or require additional devices to be worn. To treat the present situation, there is a requirement to facilitate effective and secure data communication by introducing policies that will incentivize the development of security techniques. This paper proposes a novel electrocardiogram authentication scheme which uses Legendre approximation coupled with multi-layer perceptron model for providing three levels of security for data, network and application levels. The proposed model can reach up to 99.99% testing accuracy in identifying the authorized personnel even with 5 coefficients. | |||||
BibTeX:
@article{Rathore2020,
author = {H. Rathore and C. Fu and A. Mohamed and A. Al-Ali and X. Du and M. Guizani and Z. Yu},
title = {Multi-layer security scheme for implantable medical devices},
journal = {Neural Computing and Applications},
year = {2020},
volume = {32},
doi = {https://doi.org/10.1007/s00521-018-3819-0}
}
|
|||||
| Allahham, M., Al-Sa'd, M., Al-Ali, A., Mohamed, A., Khattab, T. and Erbad, A. | DroneRF dataset: A dataset of drones for RF-based detection, classification and identification | 2019 | Data in Brief Vol. 26 |
article | DOI |
| Abstract: Modern technology has pushed us into the information age, making it easier to generate and record vast quantities of new data. Datasets can help in analyzing the situation to give a better understanding, and more importantly, decision making. Consequently, datasets, and uses to which they can be put, have become increasingly valuable commodities. This article describes the DroneRF dataset: a radio frequency (RF) based dataset of drones functioning in different modes, including off, on and connected, hovering, flying, and video recording. The dataset contains recordings of RF activities, composed of 227 recorded segments collected from 3 different drones, as well as recordings of background RF activities with no drones. The data has been collected by RF receivers that intercepts the drone's communications with the flight control module. The receivers are connected to two laptops, via PCIe cables, that runs a program responsible for fetching, processing and storing the sensed RF data in a database. An example of how this dataset can be interpreted and used can be found in the related research article “RF-based drone detection and identification using deep learning approaches: an initiative towards a large open source drone database” (Al-Sa'd et al., 2019). | |||||
BibTeX:
@article{Allahham2019,
author = {M.S. Allahham and M.F. Al-Sa'd and A. Al-Ali and A. Mohamed and T. Khattab and A. Erbad},
title = {DroneRF dataset: A dataset of drones for RF-based detection, classification and identification},
journal = {Data in Brief},
year = {2019},
volume = {26},
doi = {https://doi.org/10.1016/j.dib.2019.104313}
}
|
|||||
| Al-Sa'd, M., Al-Ali, A., Mohamed, A., Khattab, T. and Erbad, A. | RF-based drone detection and identification using deep learning approaches: An initiative towards a large open source drone database | 2019 | Future Generation Computer Systems Vol. 100 |
article | DOI |
| Abstract: The omnipresence of unmanned aerial vehicles, or drones, among civilians can lead to technical, security, and public safety issues that need to be addressed, regulated and prevented. Security agencies are in continuous search for technologies and intelligent systems that are capable of detecting drones. Unfortunately, breakthroughs in relevant technologies are hindered by the lack of open source databases for drone's Radio Frequency (RF) signals, which are remotely sensed and stored to enable developing the most effective way for detecting and identifying these drones. This paper presents a stepping stone initiative towards the goal of building a database for the RF signals of various drones under different flight modes. We systematically collect, analyze, and record raw RF signals of different drones under different flight modes such as: off, on and connected, hovering, flying, and video recording. In addition, we design intelligent algorithms to detect and identify intruding drones using the developed RF database. Three deep neural networks (DNN) are used to detect the presence of a drone, the presence of a drone and its type, and lastly, the presence of a drone, its type, and flight mode. Performance of each DNN is validated through a 10-fold cross-validation process and evaluated using various metrics. Classification results show a general decline in performance when increasing the number of classes. Averaged accuracy has decreased from 99.7% for the first DNN (2-classes), to 84.5% for the second DNN (4-classes), and lastly, to 46.8% for the third DNN (10-classes). Nevertheless, results of the designed methods confirm the feasibility of the developed drone RF database to be used for detection and identification. The developed drone RF database along with our implementations are made publicly available for students and researchers alike. | |||||
BibTeX:
@article{,
author = {M.F. Al-Sa'd and A. Al-Ali and A. Mohamed and T. Khattab and A. Erbad},
title = {RF-based drone detection and identification using deep learning approaches: An initiative towards a large open source drone database},
journal = {Future Generation Computer Systems},
year = {2019},
volume = {100},
doi = {https://doi.org/10.1016/j.future.2019.05.007}
}
|
|||||
| Belkhouja, T., Du, X., Mohamed, A., Al-Ali, A. and Guizani, M. | Biometric-based authentication scheme for Implantable Medical Devices during emergency situations | 2019 | Future Generation Computer Systems Vol. 98 |
article | DOI |
| Abstract: Biometric recognition and analysis are among the most trusted features to be used by Implantable Medical Devices (IMDs). We aim to secure these devices by using these features in emergency scenarios. As patients can witness unpredictable lethal accidents, any implantable medical device should allow access to urgent medical interventions from legitimate parties. Any delay in providing immediate medical support can endanger the patient's life. Hence, we propose in this work an authentication scheme that allows access to the implanted devices in emergency situations for only legitimate users. We have designed in the first place a scheme for authentication using Electrocardiogram instantaneous readings. Then, we joined the latter to a fixed biometric reading, which is fingerprint reading, to enable access to emergency medical teams. We have designed a scheme in a way to prevent attackers from accessing/hijacking the device even during emergency situations. This scheme has been assisted with elliptic curve cryptography to protect the wireless exchange of requested keys. The scheme relies on the instantaneous reading of the patient's heartbeat and his/her fingerprint reading to create a secure key. This key will validate the authentication request of the new medical team. We have analyzed this scheme deeply to verify that they offer the necessary security for the patient's life. We have tested if the wireless exchange of the key will expose the device's privacy. We have also tested the accuracy of the authentication process to ensure a safe and a valid performance of the authentication process. The scheme has been designed with consideration to any hardware/software limitation that characterize any implantable medical device. | |||||
BibTeX:
@article{Belkhouja2019,
author = {T. Belkhouja and X. Du and A. Mohamed and A.K. Al-Ali and M. Guizani},
title = {Biometric-based authentication scheme for Implantable Medical Devices during emergency situations},
journal = {Future Generation Computer Systems},
year = {2019},
volume = {98},
doi = {https://doi.org/10.1016/j.future.2019.02.002}
}
|
|||||
| Rathore, H., Al-Ali, A., Mohamed, A., Du, X. and Guizani, M. | A Novel Deep Learning Strategy for Classifying Different Attack Patterns for Deep Brain Implants | 2019 | IEEE Access Vol. 7 |
article | DOI |
| Abstract: Deep brain stimulators (DBSs), a widely used and comprehensively acknowledged restorative methodology, are a type of implantable medical device which uses electrical stimulation to treat neurological disorders. These devices are widely used to treat diseases such as Parkinson, movement disorder, epilepsy, and psychiatric disorders. Security in such devices plays a vital role since it can directly affect the mental, emotional, and physical state of human bodies. In worst-case situations, it can even lead to the patient's death. An adversary in such devices, for instance, can inhibit the normal functionality of the brain by introducing fake stimulation inside the human brain. Nonetheless, the adversary can impair the motor functions, alter impulse control, induce pain, or even modify the emotional pattern of the patient by giving fake stimulations through DBSs. This paper presents a deep learning methodology to predict different attack stimulations in DBSs. The proposed work uses long short-term memory, a type of recurrent network for forecasting and predicting rest tremor velocity. (A type of characteristic observed to evaluate the intensity of the neurological diseases) The prediction helps in diagnosing fake versus genuine stimulations. The effect of deep brain stimulation was tested on Parkinson tremor patients. The proposed methodology was able to detect different types of emulated attack patterns efficiently and thereby notifying the patient about the possible attack. | |||||
BibTeX:
@article{Rathore2019,
author = {H. Rathore and A.K. Al-Ali and A. Mohamed and X. Du and M. Guizani},
title = {A Novel Deep Learning Strategy for Classifying Different Attack Patterns for Deep Brain Implants},
journal = {IEEE Access},
year = {2019},
volume = {7},
doi = {https://doi.org/10.1109/ACCESS.2019.2899558}
}
|
|||||
| Shakeri, R., Al-Garadi, M., Badawy, A., Mohamed, A., Khattab, T., Al-Ali, A., Harras, K. and Guizani, M. | Design Challenges of Multi-UAV Systems in Cyber-Physical Applications: A Comprehensive Survey and Future Directions | 2019 | IEEE Communications Surveys and Tutorials Vol. 21 |
article | DOI |
| Abstract: Unmanned aerial vehicles (UAVs) have recently rapidly grown to facilitate a wide range of innovative applications that can fundamentally change the way cyber-physical systems (CPSs) are designed. CPSs are a modern generation of systems with synergic cooperation between computational and physical potentials that can interact with humans through several new mechanisms. The main advantages of using UAVs in CPS application is their exceptional features, including their mobility, dynamism, effortless deployment, adaptive altitude, agility, adjustability, and effective appraisal of real-world functions anytime and anywhere. Furthermore, from the technology perspective, UAVs are predicted to be a vital element of the development of advanced CPSs. Therefore, in this survey, we aim to pinpoint the most fundamental and important design challenges of multi-UAV systems for CPS applications. We highlight key and versatile aspects that span the coverage and tracking of targets and infrastructure objects, energy-efficient navigation, and image analysis using machine learning for fine-grained CPS applications. Key prototypes and testbeds are also investigated to show how these practical technologies can facilitate CPS applications. We present and propose state-of-the-art algorithms to address design challenges with both quantitative and qualitative methods and map these challenges with important CPS applications to draw insightful conclusions on the challenges of each application. Finally, we summarize potential new directions and ideas that could shape future research in these areas. | |||||
BibTeX:
@article{Shakeri2019,
author = {R. Shakeri and M.A. Al-Garadi and A. Badawy and A. Mohamed and T. Khattab and A.K. Al-Ali and K.A. Harras and M. Guizani},
title = {Design Challenges of Multi-UAV Systems in Cyber-Physical Applications: A Comprehensive Survey and Future Directions},
journal = {IEEE Communications Surveys and Tutorials},
year = {2019},
volume = {21},
doi = {https://doi.org/10.1109/COMST.2019.2924143}
}
|
|||||
| Belkhouja, T., Du, X., Mohamed, A., Al-Ali, A. and Guizani, M. | Symmetric encryption relying on chaotic henon system for secure hardware-friendly wireless communication of implantable medical systems | 2018 | Journal of Sensor and Actuator Networks Vol. 7 |
article | DOI |
| Abstract: Healthcare remote devices are recognized as a promising technology for treating health related issues. Among them are the wireless Implantable Medical Devices (IMDs): These electronic devices are manufactured to treat, monitor, support or replace defected vital organs while being implanted in the human body. Thus, they play a critical role in healing and even saving lives. Current IMDs research trends concentrate on their medical reliability. However, deploying wireless technology in such applications without considering security measures may offer adversaries an easy way to compromise them. With the aim to secure these devices, we explore a new scheme that creates symmetric encryption keys to encrypt the wireless communication portion. We will rely on chaotic systems to obtain a synchronized Pseudo-Random key. The latter will be generated separately in the system in such a way that avoids a wireless key exchange, thus protecting patients from the key theft. Once the key is defined, a simple encryption system that we propose in this paper will be used. We analyze the performance of this system from a cryptographic point of view to ensure that it offers a better safety and protection for patients. | |||||
BibTeX:
@article{Belkhouja2018,
author = {T. Belkhouja and X. Du and A. Mohamed and A.K. Al-Ali and M. Guizani},
title = {Symmetric encryption relying on chaotic henon system for secure hardware-friendly wireless communication of implantable medical systems},
journal = {Journal of Sensor and Actuator Networks},
year = {2018},
volume = {7},
doi = {https://doi.org/10.3390/jsan7020021}
}
|
|||||
| Elgendi, M., Al-Ali, A., Mohamed, A. and Ward, R. | Improving remote health monitoring: A low-complexity ECG compression approach | 2018 | Diagnostics Vol. 8 |
article | DOI |
| Abstract: Recent advances in mobile technology have created a shift towards using battery-driven devices in remote monitoring settings and smart homes. Clinicians are carrying out diagnostic and screening procedures based on the electrocardiogram (ECG) signals collected remotely for outpatients who need continuous monitoring. High-speed transmission and analysis of large recorded ECG signals are essential, especially with the increased use of battery-powered devices. Exploring low-power alternative compression methodologies that have high efficiency and that enable ECG signal collection, transmission, and analysis in a smart home or remote location is required. Compression algorithms based on adaptive linear predictors and decimation by a factor B/K are evaluated based on compression ratio (CR), percentage root-mean-square difference (PRD), and heartbeat detection accuracy of the reconstructed ECG signal. With two databases (153 subjects), the new algorithm demonstrates the highest compression performance (CR = 6 and PRD = 1.88) and overall detection accuracy (99.90% sensitivity, 99.56% positive predictivity) over both databases. The proposed algorithm presents an advantage for the real-time transmission of ECG signals using a faster and more efficient method, which meets the growing demand for more efficient remote health monitoring. | |||||
BibTeX:
@article{Elgendi2018,
author = {M. Elgendi and A. Al-Ali and A. Mohamed and R. Ward},
title = {Improving remote health monitoring: A low-complexity ECG compression approach},
journal = {Diagnostics},
year = {2018},
volume = {8},
doi = {https://doi.org/10.3390/diagnostics8010010}
}
|
|||||
| Fahim, A., Elbatt, T., Mohamed, A. and Al-Ali, A. | Towards Extended Bit Tracking for Scalable and Robust RFID Tag Identification Systems | 2018 | IEEE Access Vol. 6 |
article | DOI |
| Abstract: The surge in demand for Internet of Things (IoT) systems and applications has motivated a paradigm shift in the development of viable radio frequency identification technology (RFID)-based solutions for ubiquitous real-Time monitoring and tracking. Bit tracking-based anti-collision algorithms have attracted considerable attention, recently, due to its positive impact on decreasing the identification time. We aim to extend bit tracking to work effectively over erroneous channels and scalable multi RFID readers systems. Towards this objective, we extend the bit tracking technique along two dimensions. First, we introduce and evaluate a type of bit errors that appears only in bit tracking-based anti-collision algorithms called false collided bit error in single reader RFID systems. A false collided bit error occurs when a reader perceives a bit sent by tag as an erroneous bit due to channel imperfection and not because of a physical collision. This phenomenon results in a significant increase in the identification delay. We introduce a novel, zero overhead algorithm called false collided bit error selective recovery tackling the error. There is a repetition gain in bit tracking-based anti-collision algorithms due to their nature, which can be utilized to detect and correct false collided bit errors without adding extra coding bits. Second, we extend bit tracking to 'error-free' scalable mutli-reader systems, while leaving the study of multi-readers tag identification over imperfect channels for future work. We propose the multi-reader RFID tag identification using bit tracking (MRTI-BT) algorithm which allows concurrent tag identification, by neighboring RFID readers, as opposed to time-consuming scheduling. MRTI-BT identifies tags exclusive to different RFIDs, concurrently. The concept of bit tracking and the proposed parallel identification property are leveraged to reduce the identification time compared to the state-of-The-Art. | |||||
BibTeX:
@article{Fahim2018,
author = {A. Fahim and T. Elbatt and A. Mohamed and A. Al-Ali},
title = {Towards Extended Bit Tracking for Scalable and Robust RFID Tag Identification Systems},
journal = {IEEE Access},
year = {2018},
volume = {6},
doi = {https://doi.org/10.1109/ACCESS.2018.2832119}
}
|
|||||
| Rathore, H., Wenzel, L., Al-Ali, A., Mohamed, A., Du, X. and Guizani, M. | Multi-layer perceptron model on chip for secure diabetic treatment | 2018 | IEEE Access Vol. 6 |
article | DOI |
| Abstract: Diabetic patients use therapy from the insulin pump, a type of implantable medical device, for the infusion of insulin to control blood glucose level. While these devices offer many clinical benefits, there has been a recent increase in the number of cases, wherein, the wireless communication channel of such devices has been compromised. This not only causes the device to malfunction but also potentially threatens the patient's life. In this paper, a neural networks-based multi-layer perceptron model was designed for real-time medical device security. Machine learning algorithms are among the most effective and broadly utilized systems for classification, identification, and segmentation. Although they are effective, they are both computationally and memory intensive, making them hard to be deployed on low-power embedded frameworks. In this paper, we present an on-chip neural system network for securing diabetic treatment. The model achieved 98.1% accuracy in classifying fake versus genuine glucose measurements. The proposed model was comparatively evaluated with a linear support vector machine which achieved only 90.17% accuracy with negligible precision and recall. Moreover, the proposal estimates the reliability of the framework through the use of the Bayesian network. The proposed approach enhances the reliability of the overall framework by 18% when only one device is secured, and over 90% when all devices are secured. | |||||
BibTeX:
@article{Rathore2018,
author = {H. Rathore and L. Wenzel and A.K. Al-Ali and A. Mohamed and X. Du and M. Guizani},
title = {Multi-layer perceptron model on chip for secure diabetic treatment},
journal = {IEEE Access},
year = {2018},
volume = {6},
doi = {https://doi.org/10.1109/ACCESS.2018.2854822}
}
|
|||||
| Al-Ali, A., Sun, Y., Felice, M.D., Paavola, J. and Chowdhury, K. | Accessing spectrum databases using interference alignment in vehicular cognitive radio networks | 2015 | IEEE Transactions on Vehicular Technology Vol. 64 |
article | DOI |
| Abstract: Cognitive radio (CR) vehicular networks are poised to opportunistically use the licensed spectrum for high-bandwidth intervehicular messaging, driver-Assist functions, and passenger entertainment services. Recent rulings that mandate the use of spectrum databases have introduced additional challenges in this highly mobile environment, where the CR-enabled vehicles must update their spectrum data frequently and complete the data transfers with roadside base stations (BSs) in very short interaction times. This paper aims to answer two fundamental questions: 1) when to undertake local spectrum sensing, as opposed to accessing spectrum database information at a finite cost overhead; and 2) how to ensure correct packet receptions among the multiple BSs and CR vehicles using fewer slots than the messages that need to be transmitted. The contributions of this paper are twofold: First, we introduce a method of qualifying the correctness of spectrum sensing results using out-of-band 2G spectrum data using experimental results. Second, to the best of our knowledge, this is the first work on applying the concept of interference alignment (IA) in a practical network setting, leading to dramatic reduction in message transmission times. Our approach demonstrates significant reductions in the overhead of direct database queries and improvement in the accuracy of spectrum sensing for mobile vehicles. | |||||
BibTeX:
@article{,
author = {A.K. Al-Ali and Y. Sun and M. Di Felice and J. Paavola and K.R. Chowdhury},
title = {Accessing spectrum databases using interference alignment in vehicular cognitive radio networks},
journal = {IEEE Transactions on Vehicular Technology},
year = {2015},
volume = {64},
doi = {https://doi.org/10.1109/TVT.2014.2318837}
}
|
|||||
| Al-Ali, A. and Chowdhury, K. | TFRC-CR: An equation-based transport protocol for cognitive radio networks | 2013 | Ad Hoc Networks Vol. 11 |
article | DOI |
| Abstract: Reliable and high throughput data delivery in cognitive radio networks remains an open challenge owing to the inability of the source to quickly identify and react to changes in spectrum availability. The window-based rate adaptation in TCP relies on acknowledgments (ACKs) to self trigger the sending rate, which are often delayed or lost owing to intermittent primary user (PU) activity, resulting in an incorrect inference of congestion by the source node. This paper proposes the first equation-based transport protocol based on TCP Friendly Rate Control for Cognitive Radio, called as TFRC-CR, which allows immediate changes in the transmission rate based on the spectrum-related changes in the network environment. TFRC-CR has the following unique features: (i) it leverages the recent FCC mandated spectrum databases with minimum querying overhead, (ii) it enables fine adjustment of the transmission rate by identifying the instances of true network congestion, as well as (iii) provides guidelines on when to re-start the source transmission after a pause due to PU activity. TFRC-CR is evaluated through an extensive set of module additions to the ns-2 simulator which is also released for further investigation by the research community. © 2013 Elsevier B.V. All rights reserved. | |||||
BibTeX:
@article{,
author = {A.K. Al-Ali and K. Chowdhury},
title = {TFRC-CR: An equation-based transport protocol for cognitive radio networks},
journal = {Ad Hoc Networks},
year = {2013},
volume = {11},
doi = {https://doi.org/10.1016/j.adhoc.2013.04.007}
}
|
|||||
| Abdaoui, A., Al-Ali, A., Riahi, A., Mohamed, A., Du, X. and Guizani, M. | Secure medical treatment with deep learning on embedded board | 2020 | Energy Efficiency of Medical Devices and Healthcare Applications | book | DOI |
| Abstract: Deep brain stimulator is among several medical devices known by doctors and scientists for the treatment of movement disorders, such as Parkinson's disease, essential tremor, and dystonia. The security of these devices is the main concern for doctors and patients because any external attacker can introduce fake stimulation inside the human brain and then induce pain or even modify the emotional pattern of the patient. In this chapter, we design a complete prototype of an embedded system for the prediction of different attack patterns in deep brain stimulation (DBS) to mitigate intrusions to such critical devices. We propose the use of the deep-learning methodology to design a deep classifier, based on the dataset obtained from genuine measurements and attack patterns. We prove the robustness of the proposed device by emulating several random attacks on the stimulator. Results show that our system is 97% reliable to predict attacks. We also deploy the proposed system on a cloud and demonstrate the feasibility of detecting the attacks in real time. | |||||
BibTeX:
@book{Abdaoui2020,
author = {A. Abdaoui and A. Al-Ali and A. Riahi and A. Mohamed and X. Du and M. Guizani},
title = {Secure medical treatment with deep learning on embedded board},
journal = {Energy Efficiency of Medical Devices and Healthcare Applications},
year = {2020},
doi = {https://doi.org/10.1016/B978-0-12-819045-6.00007-8}
}
|
|||||
| Ghubaish, A., Salman, T., Zolanvari, M., Unal, D., Al-Ali, A. and Jain, R. | Recent Advances in the Internet of Medical Things (IoMT) Systems Security | 2023 | arXiv | generic | DOI |
| Abstract: The rapid evolutions in micro-computing, mini-hardware manufacturing, and machine to machine (M2M) communications have enabled novel Internet of Things (IoT) solutions to reshape many networking applications. Healthcare systems are among these applications that have been revolutionized with IoT, introducing an IoT branch known as the Internet of Medical Things (IoMT) systems. IoMT systems allow remote monitoring of patients with chronic diseases. Thus, it can provide timely patients' diagnostic that can save their life in case of emergencies. However, security in these critical systems is a major challenge facing their wide utilization. In this paper, we present state-of-the-art techniques to secure IoMT systems' data during collection, transmission, and storage. We comprehensively overview IoMT systems' potential attacks, including physical and network attacks. Our findings reveal that most security techniques do not consider various types of attacks. Hence, we propose a security framework that combines several security techniques. The framework covers IoMT security requirements and can mitigate most of its known attacks. | |||||
BibTeX:
@generic{Ghubaish2023,
author = {A. Ghubaish and T. Salman and M. Zolanvari and D. Unal and A. Al-Ali and R. Jain},
title = {Recent Advances in the Internet of Medical Things (IoMT) Systems Security},
journal = {arXiv},
year = {2023},
doi = {https://doi.org/10.48550/arXiv.2302.04439}
}
|
|||||
| Jouhari, M., Al-Ali, A., Baccour, E., Mohamed, A., Erbad, A., Guizani, M. and Hamdi, M. | Distributed CNN Inference on Resource-Constrained UAVs for Surveillance Systems: Design and Optimization | 2021 | arXiv | generic | DOI |
| Abstract: Unmanned Aerial Vehicles (UAVs) have attracted great interest in the last few years owing to their ability to cover large areas and access difficult and hazardous target zones, which is not the case of traditional systems relying on direct observations obtained from fixed cameras and sensors. Furthermore, thanks to the advancements in computer vision and machine learning, UAVs are being adopted for a broad range of solutions and applications. However, Deep Neural Networks (DNNs) are progressing toward deeper and complex models that prevent them from being executed on-board. In this paper, we propose a DNN distribution methodology within UAVs to enable data classification in resource-constrained devices and avoid extra delays introduced by the server-based solutions due to data communication over air-to-ground links.The proposed method is formulated as an optimization problem that aims to minimize the latency between data collection and decision-making while considering the mobility model and the resource constraints of the UAVs as part of the air-to-air communication. We also introduce the mobility prediction to adapt our system to the dynamics of UAVs and the network variation. The simulation conducted to evaluate the performance and benchmark the proposed methods, namely Optimal UAV-based Layer Distribution (OULD) and OULD with Mobility Prediction (OULD-MP), were run in an HPC cluster. The obtained results show that our optimization solution outperforms the existing and heuristic-based approaches. | |||||
BibTeX:
@generic{Jouhari2021,
author = {Jouhari, Mohammed and Al-Ali, Abdulla and Baccour, Emna and Mohamed, Amr and Erbad, Aiman and Guizani, Mohsen and Hamdi, Mounir},
title = {Distributed CNN Inference on Resource-Constrained UAVs for Surveillance Systems: Design and Optimization},
journal = {arXiv},
publisher = {arXiv},
year = {2021},
doi = {https://doi.org/10.48550/ARXIV.2105.11013}
}
|
|||||
| Abdellatif, A.A., Samara, L., Mohamed, A., Guizani, M., Erbad, A. and Al-Ali, A. | Compress or Interfere? | 2020 | arXiv | generic | DOI |
| Abstract: Rapid evolution of wireless medical devices and network technologies has fostered the growth of remote monitoring systems. Such new technologies enable monitoring patients’ medical records anytime and anywhere without limiting patients’ activities. However, critical challenges have emerged with remote monitoring systems due to the enormous amount of generated data that need to be efficiently processed and wirelessly transmitted to the service providers in time. Thus, in this paper, we leverage full-duplex capabilities for fast transmission, while tackling the trade-off between Quality of Service (QoS) requirements and consequent self-interference (SI) for efficient remote monitoring healthcare systems. The proposed framework jointly considers the residual SI resulting from simultaneous transmission and reception along with the compressibility feature of medical data in order to optimize the data transmission over wireless channels, while maintaining the application’s QoS constraint. Our simulation results demonstrate the efficiency of the proposed solution in terms of minimizing the transmission power, residual self-interference, and encoding distortion. | |||||
BibTeX:
@generic{Abdellatif2020,
author = {Abdellatif, Alaa Awad and Samara, Lutfi and Mohamed, Amr and Guizani, Mohsen and Erbad, Aiman and Al-Ali, Abdulla},
title = {Compress or Interfere?},
journal = {arXiv},
publisher = {arXiv},
year = {2020},
doi = {https://doi.org/10.48550/ARXIV.2006.15342}
}
|
|||||
| Al-Garadi, M.A., Mohamed, A., Al-Ali, A., Du, X. and Guizani, M. | A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security | 2018 | arXiv | generic | DOI |
| Abstract: The Internet of Things (IoT) integrates billions of smart devices that can communicate with one another with minimal human intervention. It is one of the fastest developing fields in the history of computing, with an estimated 50 billion devices by the end of 2020. On the one hand, IoT technologies play a crucial role in enhancing several real-life smart applications that can improve life quality. On the other hand, the crosscutting nature of IoT systems and the multidisciplinary components involved in the deployment of such systems have introduced new security challenges. Implementing security measures, such as encryption, authentication, access control, network security and application security, for IoT devices and their inherent vulnerabilities is ineffective. Therefore, existing security methods should be enhanced to secure the IoT ecosystem effectively. Machine learning and deep learning (ML/DL) have advanced considerably over the last few years, and machine intelligence has transitioned from laboratory curiosity to practical machinery in several important applications. The ability to monitor IoT devices intelligently provides a significant solution to new or zero-day attacks. ML/DL are powerful methods of data exploration for learning about 'normal' and 'abnormal' behaviour according to how IoT components and devices perform within the IoT environment. Consequently, ML/DL methods are important in transforming the security of IoT systems from merely facilitating secure communication between devices to security-based intelligence systems. The goal of this work is to provide a comprehensive survey of ML methods and recent advances in DL methods that can be used to develop enhanced security methods for IoT systems. IoT security threats that are related to inherent or newly introduced threats are presented, and various potential IoT system attack surfaces and the possible threats related to each surface are discussed. We then thoroughly review ML/DL methods for IoT security and present the opportunities, advantages and shortcomings of each method. We discuss the opportunities and challenges involved in applying ML/DL to IoT security. These opportunities and challenges can serve as potential future research directions. | |||||
BibTeX:
@generic{https://doi.org/10.48550/arxiv.1807.11023,
author = {Al-Garadi, Mohammed Ali and Mohamed, Amr and Al-Ali, Abdulla and Du, Xiaojiang and Guizani, Mohsen},
title = {A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security},
journal = {arXiv},
publisher = {arXiv},
year = {2018},
doi = {https://doi.org/10.48550/ARXIV.1807.11023}
}
|
|||||
| Shakeri, R., Al-Garadi, M.A., Badawy, A., Mohamed, A., Khattab, T., Al-Ali, A., Harras, K.A. and Guizani, M. | Design Challenges of Multi-UAV Systems in Cyber-Physical Applications: A Comprehensive Survey, and Future Directions | 2018 | arXiv | generic | DOI |
| Abstract: Unmanned Aerial Vehicles (UAVs) have recently rapidly grown to facilitate a wide range of innovative applications that can fundamentally change the way cyber-physical systems (CPSs) are designed. CPSs are a modern generation of systems with synergic cooperation between computational and physical potentials that can interact with humans through several new mechanisms. The main advantages of using UAVs in CPS application is their exceptional features, including their mobility, dynamism, effortless deployment, adaptive altitude, agility, adjustability, and effective appraisal of real-world functions anytime and anywhere. Furthermore, from the technology perspective, UAVs are predicted to be a vital element of the development of advanced CPSs. Therefore, in this survey, we aim to pinpoint the most fundamental and important design challenges of multi-UAV systems for CPS applications. We highlight key and versatile aspects that span the coverage and tracking of targets and infrastructure objects, energy-efficient navigation, and image analysis using machine learning for fine-grained CPS applications. Key prototypes and testbeds are also investigated to show how these practical technologies can facilitate CPS applications. We present and propose state-of-the-art algorithms to address design challenges with both quantitative and qualitative methods and map these challenges with important CPS applications to draw insightful conclusions on the challenges of each application. Finally, we summarize potential new directions and ideas that could shape future research in these areas. | |||||
BibTeX:
@generic{Shakeri2018,
author = {Shakeri, Reza and Al-Garadi, Mohammed Ali and Badawy, Ahmed and Mohamed, Amr and Khattab, Tamer and Al-Ali, Abdulla and Harras, Khaled A. and Guizani, Mohsen},
title = {Design Challenges of Multi-UAV Systems in Cyber-Physical Applications: A Comprehensive Survey, and Future Directions},
journal = {arXiv},
publisher = {arXiv},
year = {2018},
doi = {https://doi.org/10.48550/ARXIV.1810.09729}
}
|
|||||
| Zhou, F., Ali, A.A. and Chowdhury, K. | Investigation of TCP Protocols in Dynamically Varying Bandwidth Conditions | 2015 | Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST Vol. 156Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, pp. 176-186 |
incollection | DOI |
| Abstract: Cognitive radio (CR) networks experience fluctuating spectrum availability that impacts the end to end bandwidth of a connection. In this paper, we conduct an extensive simulation study of three different window-based TCP flavors- NewReno, Westwood+, and Compound, each of which has unique methods to determine the available bandwidth and scale the congestion window appropriately. These protocols also differ in their respective sensitivities to the metrics of round trip time, loss rate, residual buffer space, among others. These metrics exhibit divergent behavior in CR networks, as compared to classical wireless networks, owing to the frequent channel switching and spectrum sensing functions, and this influences the choice of the TCP protocol. Our ns- 3 based simulation study reveals which specific rate control mechanism in these various TCP protocols are best suited for quickly adapting to varying spectrum and bandwidth conditions, and ensuring the maximum possible throughput for the connection. | |||||
BibTeX:
@incollection{Zhou_2015,
author = {Fan Zhou and Abdulla Al Ali and Kaushik Chowdhury},
title = {Investigation of TCP Protocols in Dynamically Varying Bandwidth Conditions},
booktitle = {Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering},
journal = {Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST},
publisher = {Springer International Publishing},
year = {2015},
volume = {156},
pages = {176--186},
doi = {https://doi.org/10.1007/978-3-319-24540-9_14}
}
|
|||||
| Altamimi, E., Al-Ali, A., Malluhi, Q.M. and Al-Ali, A.K. | Energy Theft Detection Using the Wasserstein Distance on Residuals | 2023 | 2023 IEEE Texas Power and Energy Conference (TPEC) | inproceedings | DOI |
| Abstract: Detection of electricity theft improves the sustainability of the smart grid, helps electrical utilities mitigate their financial risks, and improves the overall management of resources. In this work, we utilize an LSTM neural network to forecast a given day’s energy consumption and construct residuals. The
residuals are then compared to previous residuals from normal days using the Wasserstein distance. If the Wasserstein distance for the residuals of a day exceeds a threshold, the day is highlighted to indicate suspected energy theft. Our framework can be built upon existing forecasting models with minimal computational overhead to calculate the Wasserstein distance. The framework is also highly explainable, which reduces the cost of false positives significantly. Our framework was evaluated using a public dataset and was able to detect six attack models of energy theft and faulty meters, with a false positive rate of 9% and an average F1 score of 0.91. |
|||||
BibTeX:
@inproceedings{Altamimi_2023,
author = {Emran Altamimi and Abdulaziz Al-Ali and Qutaibah M. Malluhi and Abdulla K. Al-Ali},
title = {Energy Theft Detection Using the Wasserstein Distance on Residuals},
booktitle = {2023 IEEE Texas Power and Energy Conference (TPEC)},
publisher = {IEEE},
year = {2023},
doi = {https://doi.org/10.1109/tpec56611.2023.10078584}
}
|
|||||
| Chamkhia, H., Erbad, A., Al-Ali, A., Mohamed, A., Refaey, A. and Guizani, M. | PLS Performance Analysis of a Hybrid NOMA-OMA based IoT System with Mobile Sensors | 2022 | IEEE Wireless Communications and Networking Conference, WCNC Vol. 2022-April |
inproceedings | DOI |
| Abstract: With the advent of Internet of Things (IoT) systems, privacy and integrity of messages are becoming critical issues and are threatened, especially with mobile sensors. The broadcast nature of wireless communications increase information leakage in the presence of eavesdroppers. This paper proposes a hybrid Non-Orthogonal Multiple Access (NOMA)/Orthogonal Multiple Access (OMA)- based IoT systems to improve the data transmission security of moving sensors. We derive the Key Agreement Probability (KAP) expression of the proposed scheme, and we investigate the corresponding Secrecy Outage Probability (SOP) and the Average Bit Rate (ABR), when compared to pure NOMA and pure OMA transmission schemes. Simulation results are used to validate the derived expression and to evaluate the performance of the proposed scheme in terms of KAP, SOP, and ABR. | |||||
BibTeX:
@inproceedings{Chamkhia2022,
author = {H. Chamkhia and A. Erbad and A. Al-Ali and A. Mohamed and A. Refaey and M. Guizani},
title = {PLS Performance Analysis of a Hybrid NOMA-OMA based IoT System with Mobile Sensors},
journal = {IEEE Wireless Communications and Networking Conference, WCNC},
year = {2022},
volume = {2022-April},
doi = {https://doi.org/10.1109/WCNC51071.2022.9771872}
}
|
|||||
| Abdaoui, A., Erbad, A., Al-Ali, A., Mohamed, A. and Guizani, M. | A Robust Protocol for Smart eHealthcare based on Elliptic Curve Cryptography and Fuzzy logic in IoT | 2021 | 2021 IEEE Globecom Workshops, GC Wkshps 2021 - Proceedings | inproceedings | DOI |
| Abstract: Emerging technologies change the qualities of modern healthcare by employing smart systems for patient monitoring. To well use the data surrounding the patient, tiny sensing devices and smart gateways are involved. These sensing systems have been used to collect and analyze the real-time data remotely in Internet of Medical Thinks (IoM). Since the patient sensed information is so sensitive, the security and privacy of medical data are becoming challenging problem in IoM. It is then important to ensure the security, privacy and integrity of the transmitted data by designing a secure and a lightweight authentication protocol for the IoM. In this paper, in order to improve the authentication and communications in health care applications, we present a novel secure and anonymous authentication scheme. We will use elliptic curve cryptography (ECC) with random numbers generated by fuzzy logic. We simulate IoM scheme using network simulator 3 (NS3) and we employ optimized link state routing protocol (OLSR) algorithm and ECC at each node of the network. We apply some attack algorithms such as Pollard's ρ and Baby-step Giant-step to evaluate the vulnerability of the proposed scheme. | |||||
BibTeX:
@inproceedings{Abdaoui2021,
author = {A. Abdaoui and A. Erbad and A. Al-Ali and A. Mohamed and M. Guizani},
title = {A Robust Protocol for Smart eHealthcare based on Elliptic Curve Cryptography and Fuzzy logic in IoT},
journal = {2021 IEEE Globecom Workshops, GC Wkshps 2021 - Proceedings},
year = {2021},
doi = {https://doi.org/10.1109/GCWkshps52748.2021.9682030}
}
|
|||||
| Aggarwal, M., Zubair, M., Unal, D., Al-Ali, A., Reimann, T. and Alinier, G. | A Testbed Implementation of a Biometric Identity-Based Encryption for IoMT-enabled Healthcare System | 2021 | ACM International Conference Proceeding Series | inproceedings | DOI |
| Abstract: Historically, health data was stored locally on the hospital's server as patient health records, and we had to rely on the planned check-up during doctor's visits. Now, we can monitor health continuously and in real-time. Remote healthcare monitoring can also be helpful in setting up alerts, allowing early intervention and treatment. In this way, the patient gets timely treatment, avoids doctor visits or hospitalization hassles, and reduces healthcare expenses. Additionally, in an ambulance, real-time patient data can be sent to the physician via wireless communication which can save the life of a critical patient. The critical problem that arises in Internet of Medical Things (IoMT) is how securely the health vitals can be transmitted to the physician. There are numerous ways to transmit data securely to the physician, however Identity-based cryptography is the most popular these days to provide solutions for secure transmission. Identity-based cryptography is the public key cryptography in which an arbitrary string representing an individual is used as a public key. Biometric information based public key generation by identity based encryption is a potential candidate for providing a solution to such a problem. In this work, we propose using facial biometric information of the clinicians to create a public key for encrypting health vitals of a patient. | |||||
BibTeX:
@inproceedings{Aggarwal2021,
author = {M. Aggarwal and M. Zubair and D. Unal and A. Al-Ali and T. Reimann and G. Alinier},
title = {A Testbed Implementation of a Biometric Identity-Based Encryption for IoMT-enabled Healthcare System},
journal = {ACM International Conference Proceeding Series},
year = {2021},
doi = {https://doi.org/10.1145/3508072.3508082}
}
|
|||||
| Chamkhia, H., Al-Ali, A., Mohamed, A., Guizani, M., Erbad, A. and Refaey, A. | Performance Analysis of PLS key generation-based Secure NOMA-enabled IoT Networks in the presence of Untrusted Users | 2021 | 7th IEEE World Forum on Internet of Things, WF-IoT 2021 | inproceedings | DOI |
| Abstract: In Internet of Things (IoT), a massive amount of sensitive data is generated and transmitted by IoT devices. Security risks represent a major concern in IoT, especially when using innovative techniques such as Non-Orthogonal Multiple Access (NOMA) technique, where users can access other users' data. In fact, in NOMA-based IoT systems, communication is not only threatened by external eavesdroppers, but also by untrusted internal users. Therefore, it is necessary to adopt an encryption technique that guarantees IoT system communications. This paper presents a comparative study of secret key generation, where performance analysis of secure NOMA-enabled IoT network in the presence of untrusted users is detailed using different PLS key generation schemes. | |||||
BibTeX:
@inproceedings{Chamkhia2021,
author = {H. Chamkhia and A. Al-Ali and A. Mohamed and M. Guizani and A. Erbad and A. Refaey},
title = {Performance Analysis of PLS key generation-based Secure NOMA-enabled IoT Networks in the presence of Untrusted Users},
journal = {7th IEEE World Forum on Internet of Things, WF-IoT 2021},
year = {2021},
doi = {https://doi.org/10.1109/WF-IoT51360.2021.9595800}
}
|
|||||
| Chamkhia, H., Erbad, A., Al-Ali, A., Mohamed, A., Refaey, A. and Guizani, M. | Security Performance Analysis of a Health System using Hybrid NOMA-OMA based IoT System | 2021 | 2021 IEEE Globecom Workshops, GC Wkshps 2021 - Proceedings | inproceedings | DOI |
| Abstract: Internet of Things (IoT) systems have been playing a significant role in improving the quality of various applications and services. With the expansion increase of loT devices and users, different Multiple Access (MA) techniques have been proposed to overcome the spectrum scarcity and the high latency. However, in MA-based loT systems, communication is not only threatened by external eavesdroppers but also by untrusted internal users. Therefore, proposing secured MA-based loT systems is of high importance. This paper proposes a hybrid Non Orthogonal Multiple Access (NOMA) I Orthogonal Multiple Access (OMA)-based loT system to improve the data transmission security. The proposed scheme exploits the advantages of the two different MA techniques as well as the Physical Layer Security (PLS). We first describe the system model and then we detail the proposed scheme and the relevant performance analysis. Finally, our simulation results verify the accuracy of the derived expressions and evaluate the advantage of the proposed scheme, when compared to the pure NOMA and pure OMA-based loT systems. | |||||
BibTeX:
@inproceedings{Chamkhia2021,
author = {H. Chamkhia and A. Erbad and A. Al-Ali and A. Mohamed and A. Refaey and M. Guizani},
title = {Security Performance Analysis of a Health System using Hybrid NOMA-OMA based IoT System},
journal = {2021 IEEE Globecom Workshops, GC Wkshps 2021 - Proceedings},
year = {2021},
doi = {https://doi.org/10.1109/GCWkshps52748.2021.9682100}
}
|
|||||
| Ebead, U., khalid kamal naji, Tarlochan, F., Al-Ali, A. and Du, X. | Development of diverse assessment methods for PBL implementation at a course level in Engineering Education in Qatar | 2021 | International Research Symposium on PBL | inproceedings | DOI |
| Abstract: While the current literature collectively agrees that Problem and/or Project-Based Learning (PBL) is a useful instructional methodology, the majority of the literature has been based on the assumption that all PBL stems from the same practices across engineering disciplines. In civil and structural engineering, although the current literature agrees that PBL is an effective approach, there is a lack of a clear understanding of how PBL is implemented and learning outcomes are assessed in response to different course demands. This paper reports the practices of designing diverse appropriate assessment methods to meet the different learning objectives in four PBL undergraduate courses within the civil and mechanical engineering programs at Qatar University following the principle of constructive alignment. Students from all four courses were PBL beginners, while in courses 1 and 3 the instructors were piloting PBL as their first experience. The various assessment methods were developed in response to the nature of the subject, course objectives, and students’ levels. Improved student motivation, engagement, and active participation in teamwork has been observed by all the instructors. The ongoing change initiatives toward PBL as the four courses described in the current study provide a basis for an initial change action and suggest a longer-term plan involving more instructors and students to engage in the change. The experiences shared in this study can be used as inspiration for not only engineering educators in Qatar but also higher educational educators in general. | |||||
BibTeX:
@inproceedings{Ebead_2021,
author = {Usama Ebead and khalid kamal naji and Faris Tarlochan and Abdulla Al-Ali and Xiangyun Du},
title = {Development of diverse assessment methods for PBL implementation at a course level in Engineering Education in Qatar},
journal = {International Research Symposium on PBL},
publisher = {Morressier},
year = {2021},
doi = {https://doi.org/10.26226/morressier.60ddde695d86378f03b417c1}
}
|
|||||
| Gedawy, H., Al-Ali, A., Mohamed, A., Erbad, A. and Guizani, M. | UAVs Smart heuristics for Target Coverage and Path Planning Through Strategic Locations | 2021 | 2021 International Wireless Communications and Mobile Computing, IWCMC 2021 | inproceedings | DOI |
| Abstract: The affordability and deployment-flexibility of Unmanned Air Vehicles (UAVs) have ignited the development of many smart applications, including surveillance, disaster management, and smart farming. Drone's energy consumption is a critical issue and it can be controlled through different factors, depending on the application. One approach is to minimize energy consumption by defining a minimal number of strategic target-coverage locations that the drone needs to traverse and efficiently plan the drone's route through these locations. In this paper, we provide solutions that efficiently allow UAVs to cover multiple targets using their cameras. These solutions identify a minimum set of strategic locations that cover the targets and plan the drone's routes across these locations. We address the problem with the objective of minimizing the total energy consumed by the drone during its mission. We model the problem as mixed-integer programming problem and provide a set of heuristics; with and without target clustering. We evaluate the system using simulations. The results indicate the significance of clustering in minimizing the number of strategic locations and saving the drone's energy. Moreover, flexibility in selecting cluster centers provides further reduction in the strategic locations and energy consumption. | |||||
BibTeX:
@inproceedings{Gedawy2021,
author = {H. Gedawy and A. Al-Ali and A. Mohamed and A. Erbad and M. Guizani},
title = {UAVs Smart heuristics for Target Coverage and Path Planning Through Strategic Locations},
journal = {2021 International Wireless Communications and Mobile Computing, IWCMC 2021},
year = {2021},
doi = {https://doi.org/10.1109/IWCMC51323.2021.9498662}
}
|
|||||
| Kharbach, S., Al-Ali, A., Aboumarzouk, O., Abinahed, J., Al-Ansari, A. and Younes, G. | Content Validity and User Satisfaction Evaluation of Visualization Training Tool for Surgeons for Urethral Dissection during Robot-Assisted Radical Prostatectomy | 2021 | ACM International Conference Proceeding Series | inproceedings | DOI |
| Abstract: Training and skills assessment for robotic surgeries has received unprecedented attention in technological research in the last few years due to the gradual adoption of minimally invasive robotic interventions. Robot-assisted radical prostatectomy (RARP) is one of these interventions that help cure cancer by completely removing the prostate. Trainers currently use numerous training methodologies to teach novice surgeons macro RARP skills. However, limited resources for teaching and assessing micro-skills, such as the optimal urethra dissection ranges given basic variables: prostate size and prostate cancer location, are used in practice. Therefore, we built an interactive prototype to teach these skills. This paper validates the prototype using content validity and Questionnaire for User Interaction Satisfaction (QUIS) with five surgeons. The results demonstrate high content validity and increased end-user satisfaction. | |||||
BibTeX:
@inproceedings{Kharbach2021,
author = {S. Kharbach and A. Al-Ali and O. Aboumarzouk and J. Abinahed and A. Al-Ansari and G. Younes},
title = {Content Validity and User Satisfaction Evaluation of Visualization Training Tool for Surgeons for Urethral Dissection during Robot-Assisted Radical Prostatectomy},
journal = {ACM International Conference Proceeding Series},
year = {2021},
doi = {https://doi.org/10.1145/3472813.3473192}
}
|
|||||
| Abdaoui, A., Erbad, A., Al-Ali, A., Mohamed, A. and Guizani, M. | Key Generation Based Fuzzy Logic and Elliptic Curve Cryptography for Internet of Things (IoT) Authentication | 2020 | Proceedings - 2020 International Conference on Computational Science and Computational Intelligence, CSCI 2020 | inproceedings | DOI |
| Abstract: The security and privacy of the network in the Internet of Things is playing an important challenge for researchers and engineers. Considering that packets are exchanged between the end user and the sensing devices, it is then important to ensure the security, privacy and integrity of the transmitted data by designing a secure and a lightweight authentication protocol for the IoT environment. In this paper, we present a novel method of authentication and encryption based on Elliptic Curve Cryptography (ECC) and on random numbers generated by fuzzy logic for the improvement of the authentication and the encryption in IoT systems. We evaluate our novel key generation method using standard randomness tests such as: Frequency test, Frequency test with mono block, run test, discrete Fourier transform test and advanced discrete Fourier transform test. Our results show superior performance. | |||||
BibTeX:
@inproceedings{Abdaoui2020,
author = {A. Abdaoui and A. Erbad and A. Al-Ali and A. Mohamed and M. Guizani},
title = {Key Generation Based Fuzzy Logic and Elliptic Curve Cryptography for Internet of Things (IoT) Authentication},
journal = {Proceedings - 2020 International Conference on Computational Science and Computational Intelligence, CSCI 2020},
year = {2020},
doi = {https://doi.org/10.1109/CSCI51800.2020.00194}
}
|
|||||
| Chamkhia, H., Al-Ali, A., Mohamed, A., Guizani, M., Erbad, A. and Refaey, A. | Performance Analysis of IoT Physical layer Security Using 3-D Stochastic Geometry | 2020 | Proceedings - 2020 International Conference on Computational Science and Computational Intelligence, CSCI 2020 | inproceedings | DOI |
| Abstract: The internet of things (IoT) is becoming part of the infrastructure supporting various services in every day's life. Due to the complex nature of IoT systems with heterogeneous devices, the needed security and privacy aspects are mostly ignored in the initial system design. One of the proposed solutions to address the security threats from the physical layer perspective is physical-layer security (PLS). We propose the use of 3-D stochastic geometry to accurately model IoT systems in a realistic scenarios, where sensors, access points, and eavesdroppers are randomly located in a 3-D space. We use our model with realistic system deployment parameters to conduct rigorous performance analysis for critical security metrics, such as the successful transmission probability (STP) and the secrecy outage probability (SOP) in different potential IoT scenarios. We finally utilize simulation to validate the theoretical analysis. | |||||
BibTeX:
@inproceedings{Chamkhia2020,
author = {H. Chamkhia and A. Al-Ali and A. Mohamed and M. Guizani and A. Erbad and A. Refaey},
title = {Performance Analysis of IoT Physical layer Security Using 3-D Stochastic Geometry},
journal = {Proceedings - 2020 International Conference on Computational Science and Computational Intelligence, CSCI 2020},
year = {2020},
doi = {https://doi.org/10.1109/CSCI51800.2020.00191}
}
|
|||||
| Mahgoub, A., Tarrad, N., Elsherif, R., Ismail, L. and Al-Ali, A. | Fire Alarm System for Smart Cities Using Edge Computing | 2020 | 2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020 | inproceedings | DOI |
| Abstract: The current urban planning trend is to build smart cities that are advanced, safe and sustainable. To build these cities several technologies could be exploited including the Internet of Things (IoT) and edge computing. This motivated us to develop an IoT-based fire alarm system that uses edge computing. The developed system would be suitable in smart cities, as it mitigates issues faced by the existing fire alarm systems like installation overhead and lack of remote warning. Our system is an ad-hoc network of several sensing nodes and a single central node. Each of these sensing nodes consists of an ESP8266-nodeMCU connected to different types of sensors, such as smoke, temperature, humidity, flame, Methane and Carbon Monoxide (CO) sensors. These nodes are responsible for sensing the environment and detecting fire which means that they are smart end nodes and hence satisfying one of the characteristics of edge computing. The nodes transfer their readings to a centralized node that was implemented with a Raspberry Pi computer. Communication between the sensing node and the central node is through Message Queuing Telemetry Transport (MQTT) protocol which is carried via a bridge node. When a node detects fire, it signals the centralized node to alert the user and the fire department using the attached 4G module. An SMS is sent to them and the user is called. Users can inquire about the status of their home by sending an SMS. A prototype for the system performed the desired functionalities successfully with an average delay of less than 30 seconds and a node coverage of 1400m2. | |||||
BibTeX:
@inproceedings{Mahgoub2020,
author = {A. Mahgoub and N. Tarrad and R. Elsherif and L. Ismail and A. Al-Ali},
title = {Fire Alarm System for Smart Cities Using Edge Computing},
journal = {2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020},
year = {2020},
doi = {https://doi.org/10.1109/ICIoT48696.2020.9089653}
}
|
|||||
| Naji, K., Al-Thani, H., Al-Ali, A., Ebead, U. and Du, X. | Characteristics, benefits, challenges, and socio-cultural factors of implementing pbl in qatar | 2020 | International Research Symposium on PBL | inproceedings | DOI |
| Abstract: While project-and/or problem-based learning has been implemented in higher education worldwide for several decades, both modes of PBL remain a new phenomenon in Qatar. Over the past few years, several research projects have been conducted examining the initial PBL implementation experiences and effects in Qatar. In order to provide an overall picture of implementing PBL in Qatari educational institutions, the current study provides a review of literature on how PBL has been practiced, what benefits have been perceived and documented, what challenges have been encountered, and what the future prospects are of PBL. The following research questions served as a guide for this study: What are the characteristics of PBL implementation in Qatar? What are the benefits and challenges of implementing PBL in Qatar? What socio-cultural factors have contributed to or constrained PBL implementation? Fifteen articles were selected that were appropriate for the literature analysis. The findings that emerged from the synthesis of the 15 papers included three overarching themes: preparation for change, implementation of change, and evaluation of change. Within each theme, both teachers’ and students’ perspectives were summarized. From the perspective of students, subthemes were identified including approaches to learning, views on and characteristics of collaboration, student engagement, and agency. From the perspective of teachers, the subthemes identified were readiness for change, fidelity of PBL implementation, agency development, and professional identity negotiation. In addition, socio-cultural factors contributing to and constraining the implementation of PBL were also identified and discussed. The paper concludes with recommendations on the prospects of implementing PBL in the educational system of Qatar and beyond. | |||||
BibTeX:
@inproceedings{Naji2020,
author = {K.K. Naji and H.H. Al-Thani and A.K.A.M. Al-Ali and U.A.A. Ebead and X. Du},
title = {Characteristics, benefits, challenges, and socio-cultural factors of implementing pbl in qatar},
journal = {International Research Symposium on PBL},
year = {2020},
doi = {http://hdl.handle.net/10576/39113}
}
|
|||||
| Shalaby, S., Abdellatif, A., Al-Ali, A., Mohamed, A., Erbad, A. and Guizani, M. | Performance Evaluation of Hyperledger Fabric | 2020 | 2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020 | inproceedings | DOI |
| Abstract: Blockchain is a distributed secure ledger that eliminates the need for centralized authority to store data. The centralized approach has several limitations as it is a Single-Point-of-Failure and a third-party might be needed. Blockchain, on the other hand, provides decentralized, secure and trustless framework that eliminates the need for a third party and enhances fault tolerance. In this paper, we investigate the potentials of customizing the behavior of Blockchain network based on the applications' requirements. In particular, we conduct several experiments to evaluate the performance of the Hyperledger Fabric (HLF) - a permissioned blockchain framework. Seven different scenarios were tested to depict the Blockchain behavior in terms of end-to-end transaction latency and network throughput. Moreover, in these scenarios, the impact of different parameters, such as the batch-timeout, batch size, and number of endorsing peers, has been studied. | |||||
BibTeX:
@inproceedings{Shalaby2020,
author = {S. Shalaby and A.A. Abdellatif and A. Al-Ali and A. Mohamed and A. Erbad and M. Guizani},
title = {Performance Evaluation of Hyperledger Fabric},
journal = {2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020},
year = {2020},
doi = {https://doi.org/10.1109/ICIoT48696.2020.9089614}
}
|
|||||
| Abdellatif, A., Samara, L., Mohamed, A., Al-Ali, A., Erbad, A. and Guizani, M. | Compress or Interfere? | 2019 | Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks workshops Vol. 2019-June |
inproceedings | DOI |
| Abstract: Rapid evolution of wireless medical devices and network technologies has fostered the growth of remote monitoring systems. Such new technologies enable monitoring patients' medical records anytime and anywhere without limiting patients' activities. However, critical challenges have emerged with remote monitoring systems due to the enormous amount of generated data that need to be efficiently processed and wirelessly transmitted to the service providers in time. Thus, in this paper, we leverage full-duplex capabilities for fast transmission, while tackling the trade-off between Quality of Service (QoS) requirements and consequent self-interference (SI) for efficient remote monitoring healthcare systems. The proposed framework jointly considers the residual SI resulting from simultaneous transmission and reception along with the compressibility feature of medical data in order to optimize the data transmission over wireless channels, while maintaining the application's QoS constraint. Our simulation results demonstrate the efficiency of the proposed solution in terms of minimizing the transmission power, residual self-interference, and encoding distortion. | |||||
BibTeX:
@inproceedings{Abdellatif2019,
author = {A.A. Abdellatif and L. Samara and A. Mohamed and A. Al-Ali and A. Erbad and M. Guizani},
title = {Compress or Interfere?},
journal = {Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks workshops},
year = {2019},
volume = {2019-June},
doi = {https://doi.org/10.1109/SAHCN.2019.8824824}
}
|
|||||
| Al-Emadi, S., Al-Ali, A., Mohammad, A. and Al-Ali, A. | Audio based drone detection and identification using deep learning | 2019 | 2019 15th International Wireless Communications and Mobile Computing Conference, IWCMC 2019 | inproceedings | DOI |
| Abstract: In recent years, unmanned aerial vehicles (UAVs) have become increasingly accessible to the public due to their high availability with affordable prices while being equipped with better technology. However, this raises a great concern from both the cyber and physical security perspectives since UAVs can be utilized for malicious activities in order to exploit vulnerabilities by spying on private properties, critical areas or to carry dangerous objects such as explosives which makes them a great threat to the society. Drone identification is considered the first step in a multi-procedural process in securing physical infrastructure against this threat. In this paper, we present drone detection and identification methods using deep learning techniques such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) and Convolutional Recurrent Neural Network (CRNN). These algorithms will be utilized to exploit the unique acoustic fingerprints of the flying drones in order to detect and identify them. We propose a comparison between the performance of different neural networks based on our dataset which features audio recorded samples of drone activities. The major contribution of our work is to validate the usage of these methodologies of drone detection and identification in real life scenarios and to provide a robust comparison of the performance between different deep neural network algorithms for this application. In addition, we are releasing the dataset of drone audio clips for the research community for further analysis. | |||||
BibTeX:
@inproceedings{,
author = {S. Al-Emadi and A. Al-Ali and A. Mohammad and A. Al-Ali},
title = {Audio based drone detection and identification using deep learning},
journal = {2019 15th International Wireless Communications and Mobile Computing Conference, IWCMC 2019},
year = {2019},
doi = {https://doi.org/10.1109/IWCMC.2019.8766732}
}
|
|||||
| Al-Marridi, A., Mohamed, A., Erbad, A., Al-Ali, A. and Guizani, M. | Efficient EEG mobile edge computing and optimal resource allocation for smart health applications | 2019 | 2019 15th International Wireless Communications and Mobile Computing Conference, IWCMC 2019 | inproceedings | DOI |
| Abstract: In the past few years, a rapid increase in the number of patients requiring constant monitoring, which inspires researchers to develop intelligent and sustainable remote smart healthcare services. However, the transmission of big real-time health data is a challenge since the current dynamic networks are limited by different aspects such as the bandwidth, end-to-end delay, and transmission energy. Due to this, a data reduction technique should be applied to the data before being transmitted based on the resources of the network. In this paper, we integrate efficient data reduction with wireless networking transmission to enable an adaptive compression with an acceptable distortion, while reacting to the wireless network dynamics such as channel fading and user mobility. Convolutional Auto-encoder (CAE) approach was used to implement an adaptive compression/reconstruction technique with the minimum distortion. Then, a resource allocation framework was implemented to minimize the transmission energy along with the distortion of the reconstructed signal while considering different network and applications constraints. A comparison between the results of the resource allocation framework considering both CAE and Discrete wavelet transforms (DWT) was also captured. | |||||
BibTeX:
@inproceedings{,
author = {A.Z. Al-Marridi and A. Mohamed and A. Erbad and A. Al-Ali and M. Guizani},
title = {Efficient EEG mobile edge computing and optimal resource allocation for smart health applications},
journal = {2019 15th International Wireless Communications and Mobile Computing Conference, IWCMC 2019},
year = {2019},
doi = {https://doi.org/10.1109/IWCMC.2019.8766763}
}
|
|||||
| Eldiwany, B., Abdellatif, A., Mohamed, A., Al-Ali, A., Guizani, M. and Du, X. | On Physical Layer Security in Energy-Efficient Wireless Health Monitoring Applications | 2019 | IEEE International Conference on Communications Vol. 2019-May |
inproceedings | DOI |
| Abstract: In this paper, we investigate a multi-objective optimization framework for secure wireless health monitoring applications. In particular, we consider a legitimate link for the transmission of a vital EEG signal, threatened by a passive eavesdropping attack, that aims at wiretapping these measurements. We incorporate in our framework the practical secrecy metric, namely secrecy outage probability (SOP), which requires only the knowledge of side information regarding the eavesdropper (Ev), instead of completely having its instantaneous channel state information (CSI). To that end, we formulate an optimization problem in the form of maximizing the energy efficiency of the transmitter, while minimizing the distortion encountered at the signal resulting from the compression process prior to transmission, under realistic quality of service (QoS) constraints. The problem is shown to be nonconvex and NP-complete. Towards solving the problem, a branch and bound (BnB)-based algorithm is presented where a θ-suboptimal solution, from the global optimal one, is obtained. Numerical results are conducted to verify the system performance, where it is shown that our proposed approach outperforms similar systems deploying fixed compression policies (FCPs). We successfully meet QoS requirements while optimizing the system objectives, at all channel conditions, which cannot be attained by these FCP approaches. Interestingly, we also show that a target secrecy rate can be practically achieved with nonzero probability, even when the Ev has a better channel condition, on the average, than that for the legitimate receiver. | |||||
BibTeX:
@inproceedings{Eldiwany2019,
author = {B.E. Eldiwany and A.A. Abdellatif and A. Mohamed and A. Al-Ali and M. Guizani and X. Du},
title = {On Physical Layer Security in Energy-Efficient Wireless Health Monitoring Applications},
journal = {IEEE International Conference on Communications},
year = {2019},
volume = {2019-May},
doi = {https://doi.org/10.1109/ICC.2019.8761845}
}
|
|||||
| Mahgoub, A., Tarrad, N., Elsherif, R., Al-Ali, A. and Ismail, L. | IoT-based fire alarm system | 2019 | Proceedings of the 3rd World Conference on Smart Trends in Systems, Security and Sustainability, WorldS4 2019 | inproceedings | DOI |
| Abstract: Fire alarm systems are essential in alerting people before tire engulfs their homes. However, tire alarm systems, today, require a lot of wiring and labor to be installed. This discourages users from installing them in their homes. Therefore, we are proposing an IoT based wireless fire alarm system that is easy to install. The proposed system is an ad-hoc network that consists of several nodes distributed over the house. Each of these nodes consists of a microcontroller (ESP8266 nodeMCU) connected to smoke, temperature, humidity, flame, Methane and Carbon Monoxide (CO) sensors that continuously sense the surrounding environment to detect the presence of fire. The nodes create their own Wi-Fi network. These nodes communicate with a centralized node implemented with a Raspberry Pi microcontroller integrated with a 4G module. Once fire is detected by a node, it sends a signal to a centralized node that is triggered to send an SMS to the fire department and the user, call the user and alert the house by producing a local alarm. The user can also get information about the status of his home via sending an SMS to the system. The sensing nodes create a mesh network and they are linked to the central node via a bridge node. Communication between the bridge node and the sensing node is through Message Queuing Telemetry Transport (MQTT) protocol. A prototype was developed for the proposed system and it carried out the desired functionalities successfully with an average delay of less than 30 seconds. | |||||
BibTeX:
@inproceedings{Mahgoub2019,
author = {A. Mahgoub and N. Tarrad and R. Elsherif and A. Al-Ali and L. Ismail},
title = {IoT-based fire alarm system},
journal = {Proceedings of the 3rd World Conference on Smart Trends in Systems, Security and Sustainability, WorldS4 2019},
year = {2019},
doi = {https://doi.org/10.1109/WorldS4.2019.8904001}
}
|
|||||
| Zubair, M., Unal, D., Al-Ali, A. and Shikfa, A. | Exploiting bluetooth vulnerabilities in e-health IoT devices | 2019 | ACM International Conference Proceeding Series | inproceedings | DOI |
| Abstract: Internet of Things (IoT) is an interconnected network of heterogeneous things through the Internet. The current and next generation of e-health systems are dependent on IoT devices such as wireless medical sensors. One of the most important applications of IoT devices in the medical field is the usage of these smart devices for emergency healthcare. In the current interconnected world, Bluetooth Technology plays a vital role in communication due to its less resource consumption which suits the IoT architecture and design. However Bluetooth technology does not come without security flaws. In this article, we explore various security threats in Bluetooth communication for e-Health systems and present some examples of the attacks that have been performed on e-Health systems by exploiting the identified vulnerabilities | |||||
BibTeX:
@inproceedings{Zubair2019,
author = {M. Zubair and D. Unal and A. Al-Ali and A. Shikfa},
title = {Exploiting bluetooth vulnerabilities in e-health IoT devices},
journal = {ACM International Conference Proceeding Series},
year = {2019},
doi = {https://doi.org/10.1145/3341325.3342000}
}
|
|||||
| Belkhouja, T., Mohamed, A., Al-Ali, A., Du, X. and Guizani, M. | Salt Generation for Hashing Schemes based on ECG readings for Emergency Access to Implantable Medical Devices | 2018 | 2018 International Symposium on Networks, Computers and Communications, ISNCC 2018 | inproceedings | DOI |
| Abstract: Secure communication in medical devices is a pillar in ensuring patient's safety. However, in emergency cases, this can hinder the recovery of the patient. If an emergency team cannot give themselves access to the IMD without the user's assistance, they may be unable to offer any help. This paper introduces a security scheme for similar cases. By creating a backdoor to the IMDs, legal authentication may be performed with the IMD and gain access to it. This work presents a procedure for an emergency team to validate their actions to the IMD without the need of the patient's conscious. This is ensured using hashing function and elliptic curves for the security key generation. The seed that will be used will be the heart rhythm of the patient. The authentication process introduced will only allow access to the identified parties. An eavesdropper will be unable to interfere during emergency cases and can threaten patients' lives. | |||||
BibTeX:
@inproceedings{Belkhouja2018,
author = {T. Belkhouja and A. Mohamed and A.K. Al-Ali and X. Du and M. Guizani},
title = {Salt Generation for Hashing Schemes based on ECG readings for Emergency Access to Implantable Medical Devices},
journal = {2018 International Symposium on Networks, Computers and Communications, ISNCC 2018},
year = {2018},
doi = {https://doi.org/10.1109/ISNCC.2018.8530897}
}
|
|||||
| Belkhouja, T., Mohamed, A., Al-Ali, A., Du, X. and Guizani, M. | Light-Weight Solution to Defend Implantable Medical Devices against Man-In-The-Middle Attack | 2018 | 2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings | inproceedings | DOI |
| Abstract: Nowadays, Implantable Medical Devices (IMDs) rely mainly on wireless technology for information exchange. In spite of the many advantages wireless technology offers to patients in terms of efficiency, speed and ease; it puts the patients' health in serious danger if no proper security mechanism is deployed. The IMDs rely generally on resources that are relatively simple and sometimes require surgery to be altered. Therefore, common security mechanisms cannot be simply implemented in fear of consuming all the resources held for healthcare purposes. A certain balance between security and efficiency must be found in each IMD architecture. In this work, we try to avoid encryption algorithms to protect IMDs from Man-In- The-Middle (MITM) attacks. Encryption is generally used to protect communication confidentiality. However, this method is still a subject for replay and MITM attacks. In this work, we propose to create a signature protocol that protects IMDs from MITM attempts using less resources than common encryption/decryption algorithms. This signature algorithm is dynamic, which means that the signature output depends on a key and the same message can have different signatures if this key is different. This dynamic part will be introduced using chaotic generators. | |||||
BibTeX:
@inproceedings{Belkhouja2018,
author = {T. Belkhouja and A. Mohamed and A.K. Al-Ali and X. Du and M. Guizani},
title = {Light-Weight Solution to Defend Implantable Medical Devices against Man-In-The-Middle Attack},
journal = {2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings},
year = {2018},
doi = {https://doi.org/10.1109/GLOCOM.2018.8647207}
}
|
|||||
| Rathore, H., Al-Ali, A., Mohamed, A., Du, X. and Guizani, M. | DTW based Authentication for Wireless Medical Device Security | 2018 | 2018 14th International Wireless Communications and Mobile Computing Conference, IWCMC 2018 | inproceedings | DOI |
| Abstract: Wireless medical devices play an important role in providing safety and privacy to patients suffering from major health issues. These light-weight devices can be worn inside or outside the patient's body and provide more convenience and reliable doctor-patient communication. However, the design, development, and usage of these devices play a critical role in present network paradigm. They are vulnerable to network threats and attacks which break the confidentiality, integrity and availability protocols in networking scenarios. Thus, it is important to have identification and authentication of only the authorized peoplewho can operate the device. This paper proposes Dynamic Time Warping (DTW) algorithm for providing trustedauthentication and identification of only authorized people using ECG signal. Here, DTW algorithm is used to measure the correlation between different ECG signal records. Experiments were carried out to evaluate the proposed algorithm with a large database consisting of users of al1 ages, including abnormal ECG data and long span of time intervals between ECG recordings for evaluating the reliability of the proposed algorithm. Comparative evaluation of the proposed sy stem show ed that, it is not only efficient, but also light weight in comparison to the existing systems. | |||||
BibTeX:
@inproceedings{Rathore2018,
author = {H. Rathore and A. Al-Ali and A. Mohamed and X. Du and M. Guizani},
title = {DTW based Authentication for Wireless Medical Device Security},
journal = {2018 14th International Wireless Communications and Mobile Computing Conference, IWCMC 2018},
year = {2018},
doi = {https://doi.org/10.1109/IWCMC.2018.8450419}
}
|
|||||
| Belkhouja, T., Du, X., Mohamed, A., Al-Ali, A. and Guizani, M. | New plain-text authentication secure scheme for implantable medical devices with remote control | 2017 | 2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings Vol. 2018-Janua |
inproceedings | DOI |
| Abstract: Implantable medical devices are being increasingly used to treat or monitor different medical conditions. For such purposes, wireless is the most desired communication scheme to be implemented in these devices. On the other hand, the wireless scheme increases security threats on these electronic devices, and any possibility of attack on the medical device may have lethal consequences. The patients usually have their implantable medical devices configured and monitored by their doctors. But for practical purposes, most of the time they possess a remote control for daily non-critical operations. This remote control can be considered as an open gate for attackers to target those medical devices and cause major harm. Motivated by this, we analyze in this paper the communication scheme implemented in the wireless devices, having as a starting point an Implantable Insulin Pump to develop a new protocol that can be used in the remote controlimplantable device communication, and that will rely on plain text messages to avoid encryption implementation. Finally, we will analyze how the novelties introduced with this protocol can secure such a wireless link. | |||||
BibTeX:
@inproceedings{Belkhouja2017,
author = {T. Belkhouja and X. Du and A. Mohamed and A.K. Al-Ali and M. Guizani},
title = {New plain-text authentication secure scheme for implantable medical devices with remote control},
journal = {2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings},
year = {2017},
volume = {2018-Janua},
doi = {https://doi.org/10.1109/GLOCOM.2017.8255015}
}
|
|||||
| Belkhouja, T., Mohamed, A., Al-Ali, A., Du, X. and Guizani, M. | Light-weight encryption of wireless communication for implantable medical devices using henon chaotic system | 2017 | Proceedings - 2017 International Conference on Wireless Networks and Mobile Communications, WINCOM 2017 | inproceedings | DOI |
| Abstract: Implantable Medical Devices (IMDs) are a growing industry regarding personal health care and monitoring. In addition, they provide patients with efficient treatments. In general, these devices use wireless communication technologies that may require synchronization with the medical team. Even though wireless technology offers satisfaction to the patient's daily life, it is still prone to security threats. Many malicious attacks on these devices can directly affect the patient's health in a lethal way. Using insecure wireless channels for these devices offers adversaries easy ways to steal the patient's private data and hijack these systems. This can cause damage to patients and render their devices unusable. In the aim of protecting these devices, we explore in this paper a new way to create symmetric encryption keys to encrypt the wireless communication held by the IMDs. This key generation will rely on chaotic systems to obtain synchronized Pseudo-Random keys that will be generated separately in the system. This generation is in a way that the communication channel will avoid a wireless key exchange, protecting the patient from key theft. Moreover, we will explore the performance of this generator from a cryptographic point of view, ensuring that these keys are safe to use for communication encryption. | |||||
BibTeX:
@inproceedings{Belkhouja2017,
author = {T. Belkhouja and A. Mohamed and A.K. Al-Ali and X. Du and M. Guizani},
title = {Light-weight encryption of wireless communication for implantable medical devices using henon chaotic system},
journal = {Proceedings - 2017 International Conference on Wireless Networks and Mobile Communications, WINCOM 2017},
year = {2017},
doi = {https://doi.org/10.1109/WINCOM.2017.8238203}
}
|
|||||
| Rathore, H., Al-Ali, A., Mohamed, A., Du, X. and Guizani, M. | DLRT: Deep learning approach for reliable diabetic treatment | 2017 | 2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings Vol. 2018-Janua |
inproceedings | DOI |
| Abstract: Diabetic therapy or insulin treatment enables patients to control the blood glucose level. Today, instead of physically utilizing syringes for infusing insulin, a patient can utilize a gadget, for example, a Wireless Insulin Pump (WIP) to pass insulin into the body. A typical WIP framework comprises of an insulin pump, continuous glucose management system, blood glucose monitor, and other associated devices with all connected wireless links. This takes into consideration more granular insulin conveyance while achieving blood glucose control. WIP frameworks have progressively benefited patients, yet the multifaceted nature of the subsequent framework has posed in parallel certain security implications. This paper proposes a highly accurate yet efficient deep learning methodology to protect these vulnerable devices against fake glucose dosage. Moreover, the proposal estimates the reliability of the framework through the Bayesian network. We conduct comparative study to conclude that the proposed method outperforms the state of the art by over 15% in accuracy achieving more than 93% accuracy. In addition, the proposed approach enhances the reliability of the overall system by 18% when only one wireless link is secured, and more than 90% when all wireless links are secured. | |||||
BibTeX:
@inproceedings{Rathore2017,
author = {H. Rathore and A. Al-Ali and A. Mohamed and X. Du and M. Guizani},
title = {DLRT: Deep learning approach for reliable diabetic treatment},
journal = {2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings},
year = {2017},
volume = {2018-Janua},
doi = {https://doi.org/10.1109/GLOCOM.2017.8255028}
}
|
|||||
| Rathore, H., Mohamed, A., Al-Ali, A., Du, X. and Guizani, M. | A review of security challenges, attacks and resolutions for wireless medical devices | 2017 | 2017 13th International Wireless Communications and Mobile Computing Conference, IWCMC 2017 | inproceedings | DOI |
| Abstract: Evolution of implantable medical devices for human beings has provided a radical new way for treating chronic diseases such as diabetes, cardiac arrhythmia, cochlear, gastric diseases etc. Implantable medical devices have provided a breakthrough in network transformation by enabling and accessing the technology on demand. However, with the advancement of these devices with respect to wireless communication and ability for outside caregiver to communicate wirelessly have increased its potential to impact the security, and breach in privacy of human beings. There are several vulnerable threats in wireless medical devices such as information harvesting, tracking the patient, impersonation, relaying attacks and denial of service attack. These threats violate confidentiality, integrity, availability properties of these devices. For securing implantable medical devices diverse solutions have been proposed ranging from machine learning techniques to hardware technologies. The present survey paper focusses on the challenges, threats and solutions pertaining to the privacy and safety issues of medical devices. | |||||
BibTeX:
@inproceedings{Rathore2017,
author = {H. Rathore and A. Mohamed and A. Al-Ali and X. Du and M. Guizani},
title = {A review of security challenges, attacks and resolutions for wireless medical devices},
journal = {2017 13th International Wireless Communications and Mobile Computing Conference, IWCMC 2017},
year = {2017},
doi = {https://doi.org/10.1109/IWCMC.2017.7986505}
}
|
|||||
| Shabara, Y., Mohamed, A. and Al-Ali, A. | A hardware implementation for efficient spectrum access in cognitive radio networks | 2017 | IEEE Wireless Communications and Networking Conference, WCNC | inproceedings | DOI |
| Abstract: Opportunistic spectrum access is a propitious technique to overcome the under-utilization of spectrum bands. In this work, we design an experimental test-bed for evaluating an un-slotted spectrum access scheme under real indoor environment conditions. To this end, we use the USRP software defined radio platform along with the GNURadio software that incorporates the PHY and MAC functions and modules. Our contribution is multi-fold. First, we design a MAC protocol to integrate the packet based transmission of the coexisting PU/SU network, while compensating for spectrum sensing imperfection as well as collision detection faults. Second, we evaluate the USRP-induced latency (delay) and show that it has random behavior.We work around it to obtain a fixed packet transmission time which is crucial for the channel access scheme realization and evaluation. Third, we perform helping experiments to quantify the spectrum sensing imperfection in terms of false alarm and detection probabilities. We also quantify the imperfection in collision detection. Finally, we evaluate the performance of the whole channel access scheme and compare its results to the classical sense-transmit scheme. We show that 28.5% increase in SU throughput can be achieved for the same PU packet collision rate. | |||||
BibTeX:
@inproceedings{Shabara2017,
author = {Y. Shabara and A. Mohamed and A.K. Al-Ali},
title = {A hardware implementation for efficient spectrum access in cognitive radio networks},
journal = {IEEE Wireless Communications and Networking Conference, WCNC},
year = {2017},
doi = {https://doi.org/10.1109/WCNC.2017.7925442}
}
|
|||||
| Hassan, H., Mohamed, A. and Alali, A. | DSA-based energy efficient cellular networks: Integration with the smart grid | 2016 | IEEE Vehicular Technology Conference Vol. 0 |
inproceedings | DOI |
| Abstract: Smart Grid (SG)-aware cellular networks are expected to decrease their energy consumption and consequently decrease the global carbon emissions. At the same time, cellular operators are required to meet the end-user requirements in terms of throughput. In this paper we propose a novel strategy to pave the way for the cellular operators to integrate with the SG. Our strategy is based on Dynamic Spectrum Assignment (DSA) approach. We formulate the trade-off situation of the operators as a reward function. The objective is to maximize the reward while decreasing the energy consumption. We study homogeneous, spatial-heterogeneous and spatio-temporal heterogeneous types of traffic. We study the performance of the proposed strategy in a dynamic electricity pricing context. We show that by adapting the spectrum utilization properly, the cellular operator can achieve higher rewards while using less energy compared to an operator deploying classical reuse, for low and intermediate traffic loads. We show also that the proposed DSA-based strategy is capable of adapting to the system dynamics; electricity pricing as well as end-users traffic1. | |||||
BibTeX:
@inproceedings{Hassan2016,
author = {H.K. Hassan and A. Mohamed and A. Alali},
title = {DSA-based energy efficient cellular networks: Integration with the smart grid},
journal = {IEEE Vehicular Technology Conference},
year = {2016},
volume = {0},
doi = {https://doi.org/10.1109/VTCFall.2016.7880969}
}
|
|||||
| Salama, A., Alali, A. and Mohamed, A. | An evolutionary game theoretic approach for cooperative spectrum sensing | 2016 | IEEE Wireless Communications and Networking Conference, WCNC Vol. 2016-Septe |
inproceedings | DOI |
| Abstract: Many spectrum sensing techniques have been proposed to allow a secondary user (SU) to utilize a primary user's (PU) spectrum through opportunistic access. However, few of them have considered the tradeoff between accuracy and energy consumption by taking into account the selfishness of the (SUs) in a distributed network. In this work, we consider spectrum sensing as a game where the payoff is the throughput of each SU/player. Each SU chooses between two actions, parallel individual sensing and sequential cooperative sensing techniques. Using those techniques, each SU will distributively decide the existence of the PU. Due to the repetitive nature of our game, we model it using evolutionary game (EG) theory which provides a suitable model that describes the behavioral evolution of the actions taken by the SUs. We address our problem in two cases, when the players are homogeneous and heterogeneous respectively. For the sake of stability, we find the equilibria that lead to evolutionary stable strategies (ESS) by proving that our system is evolutionary asymptotically stable, in both cases, under certain conditions on the sensing time and the false alarm probability. | |||||
BibTeX:
@inproceedings{Salama2016,
author = {A.M. Salama and A. Alali and A. Mohamed},
title = {An evolutionary game theoretic approach for cooperative spectrum sensing},
journal = {IEEE Wireless Communications and Networking Conference, WCNC},
year = {2016},
volume = {2016-Septe},
doi = {https://doi.org/10.1109/WCNC.2016.7564914}
}
|
|||||
| Al-Ali, A. and Chowdhury, K. | Simulating dynamic spectrum access using ns-3 for wireless networks in smart environments | 2014 | 2014 11th Annual IEEE International Conference on Sensing, Communication, and Networking Workshops, SECON Workshops 2014 | inproceedings | DOI |
| Abstract: Sudden spectrum demands may occur in dense and congested cities, which stress the communication infrastructure. At these times, identifying alternate spectrum bands through cognitive radio (CR) technology will allow users to maintain connectivity and relieve data congestion in the unlicensed bands. However, deployment of the CR networks must be preceded by accurate simulation of these networks, given the high infrastructure costs involved in their installation. Moreover, CR protocols are often cross-layered, which cannot be trivially implemented in off-the-shelf hardware. This paper proposes a framework for the network simulator 3 (ns-3) that is suitable for large networks. Our approach introduces several CR capabilities, such as spectrum sensing, primary user detection, and spectrum hand-off. Our simulator demonstrates improvements in execution time and memory usage, when compared to the earlier versions implemented for the ns-2 environment. This paper is accompanied by the release of the full source code for further research and improvement. | |||||
BibTeX:
@inproceedings{,
author = {A. Al-Ali and K. Chowdhury},
title = {Simulating dynamic spectrum access using ns-3 for wireless networks in smart environments},
journal = {2014 11th Annual IEEE International Conference on Sensing, Communication, and Networking Workshops, SECON Workshops 2014},
year = {2014},
doi = {https://doi.org/10.1109/SECONW.2014.6979701}
}
|
|||||
| Al-Ali, A., Chowdhury, K., Felice, M.D. and Paavola, J. | Querying spectrum databases and improved sensing for vehicular cognitive radio networks | 2014 | 2014 IEEE International Conference on Communications, ICC 2014 | inproceedings | DOI |
| Abstract: Cognitive radio (CR) vehicular networks are poised to opportunistically use the licensed spectrum for high bandwidth inter-vehicular messaging, driver-assist functions, and passenger entertainment services. Recent rulings that mandate the use of spectrum databases introduce additional challenges in this highly mobile environment, where the CR enabled vehicles must update their spectrum data frequently and complete the data transfers with roadside base stations. As the rules allow local spectrum sensing only under the assurance of high accuracy, there is an associated tradeoff in obtaining assuredly correct spectrum updates from the database at a finite cost, compared to locally obtained sensing results that may have a finite error probability. This paper aims to answer the question of when to undertake local spectrum sensing and when to rely on database updates through a novel method of exploiting the correlation between 2G spectrum bands and TV whitespace. We describe experimental studies that validate our approach and quantify the cost savings made possible by intermittent database queries. © 2014 IEEE. | |||||
BibTeX:
@inproceedings{,
author = {A. Al-Ali and K. Chowdhury and M. Di Felice and J. Paavola},
title = {Querying spectrum databases and improved sensing for vehicular cognitive radio networks},
journal = {2014 IEEE International Conference on Communications, ICC 2014},
year = {2014},
doi = {https://doi.org/10.1109/ICC.2014.6883514}
}
|
|||||
| Al-Ali, A. and Chowdhury, K. | TFRC-CR: An equation-based transport protocol for cognitive radio networks | 2013 | 2013 International Conference on Computing, Networking and Communications, ICNC 2013 | inproceedings | DOI |
| Abstract: Data delivery in a dynamically changing spectrum environment continues to remain an unsolved problem, with existing TCP based implementations falling short owing to their inability to react swiftly to spectrum changes. This paper proposes the first equation-based transport protocol, based on the TCP Friendly Rate Control (TFRC) protocol, which uses the recent FCC mandated spectrum database information instead of relying on any intermediate node feedback. Not only does this approach maintain the strict end to end property required at this layer of the protocol stack, but also allows fine adjustment of the transmission rate through continuous adaptation. We explore interesting directions on how to limit repeated queries to the spectrum database and yet allow the source to control the rate effectively; when to re-start the transmissions; and how to interpret possible spectrum changes in the intermediate nodes correctly without mistaking it for normal network congestion, among others. Our extension to the ns-2 simulator enables thorough testing of various aspects of our protocol adapted for cognitive radio, called as TFRC-CR. We show through simulation an improvement of over 33% in the end to end throughput when compared with the classical TFRC. © 2013 IEEE. | |||||
BibTeX:
@inproceedings{,
author = {A.K. Al-Ali and K. Chowdhury},
title = {TFRC-CR: An equation-based transport protocol for cognitive radio networks},
journal = {2013 International Conference on Computing, Networking and Communications, ICNC 2013},
year = {2013},
doi = {https://doi.org/10.1109/ICCNC.2013.6504070}
}
|
|||||
| Sellami, A.L., Al-Ali, A., Allouh, A. and Alhazbi, S. | Student Attitudes and Interests in STEM in Qatar through the Lens of the Social Cognitive Theory | 2023 | Sustainability | article | |
| Abstract: STEM (science, technology, engineering, and math) has taken center stage as a priority policy agenda for Qatar’s leadership. At present, STEM stands as a fundamental catalyst for Qatar’s sustainable economic, environmental, human, and social development goals, as is outlined in the Qatar National Vision 2030. The aim of this exploratory study was to investigate the determinants of students’ interest in pursuing Science, Technology, Engineering, and Mathematics (STEM) studies and eventual careers in Qatar. This study used a survey involving a representative sample of a total of 425 students from public (government-funded) middle schools in the country. Data for this research were gathered using a survey distributed to students in grades 7, 8, and 9. Guided by the Social Cognitive Theory, a survey was implemented with a view to investigating the intrinsic and extrinsic factors likely to contribute to student STEM educational and career interest. Two main statistical tests were carried out: independent sample t-tests and one way ANOVA. Results derived from the study reveal that gender, nationality, and parental education and occupation served as predictors of student interest in a STEM degree or profession. The results derived from this study have important implications for STEM-related fields of study and career. | |||||
BibTeX:
@article{Sellami2023,
author = {Abdel Latif Sellami and Abdulla Al-Ali and Amani Allouh and Saleh Alhazbi},
title = {Student Attitudes and Interests in STEM in Qatar through the Lens of the Social Cognitive Theory},
journal = {Sustainability},
year = {2023}
}
|
|||||