Privacy-Aware Single-Nucleotide Polymorphisms (SNPs) Using Bilinear Group Accumulators in Batch Mode
Conference Proceeding
Buchanan, W., Grierson, S., & Uribe, D. (2024)
Privacy-Aware Single-Nucleotide Polymorphisms (SNPs) Using Bilinear Group Accumulators in Batch Mode. In Proceedings of the 10th International Conference on Information Systems Security and Privacy (226-233). https://doi.org/10.5220/0012454300003648
Biometric data is often highly sensitive, and a leak of this data can lead to serious privacy breaches. Some of the most sensitive of this type of data relates to the usage of...
Design and Evaluation of Memory Efficient Data Structure Scheme for Energy Drainage Attacks in Wireless Sensor Networks
Journal Article
Bhatti, D. S., Saleem, S., Ali, Z., Park, T., Suh, B., Kamran, A., …Kim, K. (2024)
Design and Evaluation of Memory Efficient Data Structure Scheme for Energy Drainage Attacks in Wireless Sensor Networks. IEEE Access, 12, 41499-41516. https://doi.org/10.1109/access.2024.3377144
Wireless Sensor Networks (WSN) are deployed on a large scale and require protection from malicious energy drainage attacks, particularly those directed at the routing layer. T...
PHASER: Perceptual Hashing Algorithms Evaluation and Results -an Open Source Forensic Framework
Journal Article
Mckeown, S., Aaby, P., & Steyven, A. (2024)
PHASER: Perceptual Hashing Algorithms Evaluation and Results -an Open Source Forensic Framework. Forensic Science International: Digital Investigation, 48(Supplement), Article 301680
The automated comparison of visual content is a contemporary solution to scale the detection of illegal media and extremist material, both for detection on individual devices ...
A Probability Mapping-Based Privacy Preservation Method for Social Networks
Conference Proceeding
Li, Q., Wang, Y., Wang, F., Tan, Z., & Wang, C. (2024)
A Probability Mapping-Based Privacy Preservation Method for Social Networks. . https://doi.org/10.1007/978-981-97-1274-8_19
The mining and analysis of social networks can bring significant economic and social benefits. However, it also poses a risk of privacy leakages. Differential privacy is a de ...
SkipGateNet: A Lightweight CNN-LSTM Hybrid Model with Learnable Skip Connections for Efficient Botnet Attack Detection in IoT
Journal Article
Alshehri, M. S., Ahmad, J., Almakdi, S., Qathrady, M. A., Ghadi, Y. Y., & Buchanan, W. J. (2024)
SkipGateNet: A Lightweight CNN-LSTM Hybrid Model with Learnable Skip Connections for Efficient Botnet Attack Detection in IoT. IEEE Access, 12, https://doi.org/10.1109/access.2024.3371992
The rise of Internet of Things (IoT) has led to increased security risks, particularly from botnet attacks that exploit IoT device vulnerabilities. This situation necessitates...
Reliable and Fair Trustworthiness Evaluation Protocol for Platoon Service Recommendation System
Journal Article
Cheng, H., Tan, Z., Zhang, X., & Liu, Y. (in press)
Reliable and Fair Trustworthiness Evaluation Protocol for Platoon Service Recommendation System. Chinese Journal of Electronics,
Aiming at the problems of the communication inefficiency and high energy consumption in vehicular networks, the platoon service recommendation systems (PSRS) are presented. Ma...
STIDNet: Identity-Aware Face Forgery Detection with Spatiotemporal Knowledge Distillation
Journal Article
Fang, M., Yu, L., Xie, H., Tan, Q., Tan, Z., Hussain, A., …Tian, Z. (in press)
STIDNet: Identity-Aware Face Forgery Detection with Spatiotemporal Knowledge Distillation. IEEE Transactions on Computational Social Systems, https://doi.org/10.1109/tcss.2024.3356549
The impressive development of facial manipulation techniques has raised severe public concerns. Identity-aware methods, especially suitable for protecting celebrities, are see...
Can Federated Models Be Rectified Through Learning Negative Gradients?
Conference Proceeding
Tahir, A., Tan, Z., & Babaagba, K. O. (2024)
Can Federated Models Be Rectified Through Learning Negative Gradients?. In Big Data Technologies and Applications (18-32). https://doi.org/10.1007/978-3-031-52265-9_2
Federated Learning (FL) is a method to train machine learning (ML) models in a decentralised manner, while preserving the privacy of data from multiple clients. However, FL is...
Machine Un-learning: An Overview of Techniques, Applications, and Future Directions
Journal Article
Sai, S., Mittal, U., Chamola, V., Huang, K., Spinelli, I., Scardapane, S., …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. Howev...
Hybrid Threats, Cyberterrorism and Cyberwarfare
Book
Ferrag, M. A., Kantzavelou, I., Maglaras, L., & Janicke, H. (Eds.)
(2024). Hybrid Threats, Cyberterrorism and Cyberwarfare. Boca Raton: CRC Press. https://doi.org/10.1201/9781003314721
Nowadays in cyberspace, there is a burst of information to which everyone has access. However, apart from the advantages the internet offers, it also hides numerous dangers fo...