Outputs (234)

IoT Authentication Protocols: Challenges, and Comparative Analysis (2025)
Journal Article
Alsheavi, A., Hawbani, A., Othman, W., Wang, X., Qaid, G. R. S., Zhao, L., Al-Dubai, A., Liu, Z., Ismail, A., Haveri, R. H., Alsamhi, S. H., & Al-Qaness, M. A. A. (2025). IoT Authentication Protocols: Challenges, and Comparative Analysis. ACM computing surveys, 57(5), Article 116. https://doi.org/10.1145/3703444

In the ever-evolving information technology landscape, the Internet of Things (IoT) is a groundbreaking concept that bridges the physical and digital worlds. It is the backbone of an increasingly sophisticated interactive environment, yet it is a sub... Read More about IoT Authentication Protocols: Challenges, and Comparative Analysis.

A True Random Number Generator Based On Race Hazard And Jitter Of Braided And Cross-Coupled Logic Gates Using FPGA (2024)
Journal Article
Ahmed, H. O., Kim, D., & Buchanan, B. (in press). A True Random Number Generator Based On Race Hazard And Jitter Of Braided And Cross-Coupled Logic Gates Using FPGA. IEEE Access, 12, 182943-182955. https://doi.org/10.1109/ACCESS.2024.3512419

In the contemporary digital landscape, security has become a vital element of our existence. The growing volume of sensitive information being stored and transmitted over networks necessitates the implementation of robust security measures. Cryptogra... Read More about A True Random Number Generator Based On Race Hazard And Jitter Of Braided And Cross-Coupled Logic Gates Using FPGA.

An Enhanced and Robust Data Publishing Scheme for Private and Useful 1:M Microdata (2024)
Journal Article
Rizwan, M., Hawbani, A., Xingfu, W., Anjum, A., Angin, P., Sever, Y., Chen, S., Zhao, L., & Al-Dubai, A. (online). An Enhanced and Robust Data Publishing Scheme for Private and Useful 1:M Microdata. IEEE Transactions on Big Data, https://doi.org/10.1109/TBDATA.2024.3495497

A data publishing deal conducted with anonymous microdata can preserve the privacy of people. However, anonymizing data with multiple records of an individual (1:M dataset) is still a challenging problem. After anonymizing the 1:M microdata, the vert... Read More about An Enhanced and Robust Data Publishing Scheme for Private and Useful 1:M Microdata.

CAST: Efficient Traffic Scenario Inpainting in Cellular Vehicle-to-Everything Systems (2024)
Journal Article
Zhao, L., Mao, C., Wan, S., Hawbani, A., Al-Dubai, A. Y., Min, G., & Zomaya, A. Y. (online). CAST: Efficient Traffic Scenario Inpainting in Cellular Vehicle-to-Everything Systems. IEEE Transactions on Mobile Computing, https://doi.org/10.1109/tmc.2024.3492148

As a promising vehicular communication technology, Cellular Vehicle-to-Everything (C-V2X) is expected to ensure the safety and convenience of Intelligent Transportation Systems (ITS) by providing global road information. However, it is difficult to o... Read More about CAST: Efficient Traffic Scenario Inpainting in Cellular Vehicle-to-Everything Systems.

Novel Lagrange Multipliers-Driven Adaptive Offloading for Vehicular Edge Computing (2024)
Journal Article
Zhao, L., Li, T., Meng, G., Hawbani, A., Min, G., Al-Dubai, A., & Zomaya, A. (2024). Novel Lagrange Multipliers-Driven Adaptive Offloading for Vehicular Edge Computing. IEEE Transactions on Computers, 73(12), 2868-2881. https://doi.org/10.1109/TC.2024.3457729

Vehicular Edge Computing (VEC) is a transportation-specific version of Mobile Edge Computing (MEC) designed for vehicular scenarios. Task offloading allows vehicles to send computational tasks to nearby Roadside Units (RSUs) in order to reduce the co... Read More about Novel Lagrange Multipliers-Driven Adaptive Offloading for Vehicular Edge Computing.

User Preferences-Based Proactive Content Caching with Characteristics Differentiation in HetNets (2024)
Journal Article
Lin, N., Wang, Y., Zhang, E., Wan, S., Al-Dubai, A., & Zhao, L. (online). User Preferences-Based Proactive Content Caching with Characteristics Differentiation in HetNets. IEEE Transactions on Sustainable Computing, https://doi.org/10.1109/TSUSC.2024.3441606

With the proliferation of mobile applications, the explosion of mobile data traffic imposes a significant burden on backhaul links with limited capacity in heterogeneous cellular networks (HetNets). To alleviate this challenge, content caching based... Read More about User Preferences-Based Proactive Content Caching with Characteristics Differentiation in HetNets.

A Novel Autonomous Adaptive Frame Size for Time-Slotted LoRa MAC Protocol (2024)
Journal Article
Alahmadi, H., Bouabdallah, F., Al-Dubai, A., & Ghaleb, B. (2024). A Novel Autonomous Adaptive Frame Size for Time-Slotted LoRa MAC Protocol. IEEE Transactions on Industrial Informatics, 20(10), 12284-12293. https://doi.org/10.1109/tii.2024.3417308

LoRa networks represent a promising technology for IoT applications due to their long range, low cost, and energy efficiency. However, their ALOHA-based access method and duty cycle restrictions can limit their scalability and reliability in high-den... Read More about A Novel Autonomous Adaptive Frame Size for Time-Slotted LoRa MAC Protocol.

Reliable and Fair Trustworthiness Evaluation Protocol for Platoon Service Recommendation System (2024)
Journal Article
Cheng, H., Tan, Z., Zhang, X., & Liu, Y. (online). Reliable and Fair Trustworthiness Evaluation Protocol for Platoon Service Recommendation System. Chinese Journal of Electronics, https://doi.org/10.23919/cje.2023.00.012

Aiming at the problems of the communication inefficiency and high energy consumption in vehicular networks, the platoon service recommendation systems (PSRS) are presented. Many schemes for evaluating the reputation of platoon head vehicles have been... Read More about Reliable and Fair Trustworthiness Evaluation Protocol for Platoon Service Recommendation System.

Adaptive Mobile Chargers Scheduling Scheme based on AHP-MCDM for WRSN (2024)
Journal Article
Makanda, K., Hawbani, A., Wang, . X., Naji, A., Al-Dubai, A., Zhao, L., & Alsamhi, S. H. (online). Adaptive Mobile Chargers Scheduling Scheme based on AHP-MCDM for WRSN. IEEE Transactions on Sustainable Computing, https://doi.org/10.1109/TSUSC.2024.3391316

Wireless Sensor Networks (WSNs) are used to sense and monitor physical conditions in various services and applications.
However, there are a number of challenges in deploying WSNs, especially those pertaining to energy replenishment. Using the curre... Read More about Adaptive Mobile Chargers Scheduling Scheme based on AHP-MCDM for WRSN.

Wireless Power Transfer Technologies, Applications, and Future Trends: A Review (2024)
Journal Article
Alabsi, A., Hawbani, A., Wang, X., Al-Dubai, A., Hu, J., Aziz, S. A., Kumar, S., Zhao, L., Shvetsov, A. V., & Alsamhi, S. H. (online). Wireless Power Transfer Technologies, Applications, and Future Trends: A Review. IEEE Transactions on Sustainable Computing, https://doi.org/10.1109/TSUSC.2024.3380607

Wireless Power Transfer (WPT) is a disruptive technology that allows wireless energy provisioning for energy- limited IoT devices, thus decreasing the over-reliance on batteries and wires. WPT could replace conventional energy provisioning (e.g., ene... Read More about Wireless Power Transfer Technologies, Applications, and Future Trends: A Review.

Machine Un-learning: An Overview of Techniques, Applications, and Future Directions (2023)
Journal Article
Sai, S., Mittal, U., Chamola, V., Huang, K., Spinelli, I., Scardapane, S., Tan, Z., & Hussain, A. (2024). Machine Un-learning: An Overview of Techniques, Applications, and Future Directions. Cognitive Computation, 16, 482-506. https://doi.org/10.1007/s12559-023-10219-3

ML applications proliferate across various sectors. Large internet firms employ ML to train intelligent models using vast datasets, including sensitive user information. However, new regulations like GDPR require data removal by businesses. Deleting... Read More about Machine Un-learning: An Overview of Techniques, Applications, and Future Directions.

Navigating Industry 5.0: A Survey of Key Enabling Technologies, Trends, Challenges, and Opportunities (2023)
Journal Article
Tallat,, R., Hawbani, A., Wang, X., Al-Dubai, A., Zhao, L., Liu, Z., Min, G., Zomaya, A., & Alsamhi, S. (2024). Navigating Industry 5.0: A Survey of Key Enabling Technologies, Trends, Challenges, and Opportunities. Communications Surveys and Tutorials, IEEE Communications Society, 26(2), 1080 - 1126. https://doi.org/10.1109/comst.2023.3329472

This century has been a major avenue for revolutionary changes in technology and industry. Industries have transitioned towards intelligent automation, relying less on human intervention, resulting in the fourth industrial revolution, Industry 4.0. T... Read More about Navigating Industry 5.0: A Survey of Key Enabling Technologies, Trends, Challenges, and Opportunities.

Rapidrift: Elementary Techniques to Improve Machine Learning-Based Malware Detection (2023)
Journal Article
Manikandaraja, A., Aaby, P., & Pitropakis, N. (2023). Rapidrift: Elementary Techniques to Improve Machine Learning-Based Malware Detection. Computers, 12(10), Article 195. https://doi.org/10.3390/computers12100195

Artificial intelligence and machine learning have become a necessary part of modern living along with the increased adoption of new computational devices. Because machine learning and artificial intelligence can detect malware better than traditional... Read More about Rapidrift: Elementary Techniques to Improve Machine Learning-Based Malware Detection.

A Digital Twin-Assisted Intelligent Partial Offloading Approach for Vehicular Edge Computing (2023)
Journal Article
Zhao, L., Zhao, Z., Zhang, E., Hawbani, A., Al-Dubai, A., Tan, Z., & Hussain, A. (2023). A Digital Twin-Assisted Intelligent Partial Offloading Approach for Vehicular Edge Computing. IEEE Journal on Selected Areas in Communications, 41(11), 3386-3400. https://doi.org/10.1109/jsac.2023.3310062

Vehicle Edge Computing (VEC) is a promising paradigm that exposes Mobile Edge Computing (MEC) to road scenarios. In VEC, task offloading can enable vehicles to offload the computing tasks to nearby Roadside Units (RSUs) that deploy computing capabili... Read More about A Digital Twin-Assisted Intelligent Partial Offloading Approach for Vehicular Edge Computing.

Reliable and Scalable Routing Under Hybrid SDVN Architecture: A Graph Learning Based Method (2023)
Journal Article
Li, Z., Zhao, L., Min, G., Al-Dubai, A. Y., Hawbani, A., Zomaya, A. Y., & Luo, C. (2023). Reliable and Scalable Routing Under Hybrid SDVN Architecture: A Graph Learning Based Method. IEEE Transactions on Intelligent Transportation Systems, 24(12), 14022 - 14036. https://doi.org/10.1109/tits.2023.3300082

Greedy routing efficiently achieves routing solutions for vehicular networks due to its simplicity and reliability. However, the existing greedy routing schemes have mainly considered simple routing metrics only, e.g., distance based on the local vie... Read More about Reliable and Scalable Routing Under Hybrid SDVN Architecture: A Graph Learning Based Method.

A Transcriptomic Appreciation of Childhood Meningococcal and Polymicrobial Sepsis from a Pro-Inflammatory and Trajectorial Perspective, a Role for Vascular Endothelial Growth Factor A and B Modulation? (2023)
Journal Article
Rashid, A., Brusletto, B. S., Al-Obeidat, F., Toufiq, M., Benakatti, G., Brierley, J., Malik, Z. A., Hussain, Z., Alkhazaimi, H., Sharief, J., Kadwa, R., Sarpal, A., Chaussabel, D., Malik, R. A., Quraishi, N., Khilnani, P., Zaki, S. A., Nadeem, R., Shaikh, G., Al-Dubai, A., …Hussain, A. (2023). A Transcriptomic Appreciation of Childhood Meningococcal and Polymicrobial Sepsis from a Pro-Inflammatory and Trajectorial Perspective, a Role for Vascular Endothelial Growth Factor A and B Modulation?. Shock, 60(4), 503-516. https://doi.org/10.1097/shk.0000000000002192

This study investigated the temporal dynamics of childhood sepsis by analyzing gene expression changes associated with proinflammatory processes. Five datasets, including four meningococcal sepsis shock (MSS) datasets (two temporal and two longitudin... Read More about A Transcriptomic Appreciation of Childhood Meningococcal and Polymicrobial Sepsis from a Pro-Inflammatory and Trajectorial Perspective, a Role for Vascular Endothelial Growth Factor A and B Modulation?.

ESPP: Efficient Sector-based Charging Scheduling and Path Planning for WRSNs with Hexagonal Topology (2023)
Journal Article
Naji, A., Hawbani, A., Wang, X., Al-Gunid, H. M., Al-Dhabi, Y., Al-Dubai, A., Hussain, A., Zhao, L., & Alsamhi, S. H. (2024). ESPP: Efficient Sector-based Charging Scheduling and Path Planning for WRSNs with Hexagonal Topology. IEEE Transactions on Sustainable Computing, 9(1), 31 - 45. https://doi.org/10.1109/tsusc.2023.3296607

Wireless Power Transfer (WPT) is a promising technology that can potentially mitigate the energy provisioning problem for sensor networks. In order to efficiently replenish energy for these battery-powered devices, designing appropriate scheduling an... Read More about ESPP: Efficient Sector-based Charging Scheduling and Path Planning for WRSNs with Hexagonal Topology.

MESON: A Mobility-aware Dependent Task Offloading Scheme for Urban Vehicular Edge Computing (2023)
Journal Article
Zhao, L., Zhang, E., Wan, S., Hawbani, A., Al-Dubai, A. Y., Min, G., & Zomaya, A. Y. (2024). MESON: A Mobility-aware Dependent Task Offloading Scheme for Urban Vehicular Edge Computing. IEEE Transactions on Mobile Computing, 23(5), 4259 - 4272. https://doi.org/10.1109/tmc.2023.3289611

Vehicular Edge Computing (VEC) is the transportation version of Mobile Edge Computing (MEC) in road scenarios. One key technology of VEC is task offloading, which allows vehicles to send their computation tasks to the surrounding Roadside Units (RSUs... Read More about MESON: A Mobility-aware Dependent Task Offloading Scheme for Urban Vehicular Edge Computing.

MedOptNet: Meta-Learning Framework for Few-shot Medical Image Classification (2023)
Journal Article
Lu, L., Cui, X., Tan, Z., & Wu, Y. (2024). MedOptNet: Meta-Learning Framework for Few-shot Medical Image Classification. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 21(4), 725-736. https://doi.org/10.1109/TCBB.2023.3284846

In the medical research domain, limited data and high annotation costs have made efficient classification under few-shot conditions a popular research area. This paper proposes a meta-learning framework, termed MedOptNet, for few-shot medical image c... Read More about MedOptNet: Meta-Learning Framework for Few-shot Medical Image Classification.

Hamming Distributions of Popular Perceptual Hashing Techniques (2023)
Journal Article
McKeown, S., & Buchanan, W. J. (2023). Hamming Distributions of Popular Perceptual Hashing Techniques. Forensic Science International: Digital Investigation, 44(Supplement), Article 301509. https://doi.org/10.1016/j.fsidi.2023.301509

Content-based file matching has been widely deployed for decades, largely for the detection of sources of copyright infringement, extremist materials, and abusive sexual media. Perceptual hashes, such as Microsoft's PhotoDNA, are one automated mechan... Read More about Hamming Distributions of Popular Perceptual Hashing Techniques.