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 ...
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...
Preserving Differential Privacy in Deep Learning Based on Feature Relevance Region Segmentation
Journal Article
Wang, F., Xie, M., Tan, Z., Li, Q., & Wang, C. (2024)
Preserving Differential Privacy in Deep Learning Based on Feature Relevance Region Segmentation. IEEE Transactions on Emerging Topics in Computing, 12(1), 307 - 315. https://doi.org/10.1109/TETC.2023.3244174
In the era of big data, deep learning techniques provide intelligent solutions for various problems in real-life scenarios. However, deep neural networks depend on large-scale...
Ensemble learning-based IDS for sensors telemetry data in IoT networks
Journal Article
Naz, N., Khan, M. A., Alsuhibany, S. A., Diyan, M., Tan, Z., Khan, M. A., & Ahmad, J. (2022)
Ensemble learning-based IDS for sensors telemetry data in IoT networks. Mathematical Biosciences and Engineering, 19(10), 10550-10580. https://doi.org/10.3934/mbe.2022493
The Internet of Things (IoT) is a paradigm that connects a range of physical smart devices to provide ubiquitous services to individuals and automate their daily tasks. IoT de...
A novel flow-vector generation approach for malicious traffic detection
Journal Article
Hou, J., Liu, F., Lu, H., Tan, Z., Zhuang, X., & Tian, Z. (2022)
A novel flow-vector generation approach for malicious traffic detection. Journal of Parallel and Distributed Computing, 169, 72-86. https://doi.org/10.1016/j.jpdc.2022.06.004
Malicious traffic detection is one of the most important parts of cyber security. The approaches of using the flow as the detection object are recognized as effective. Benefit...
Blockchain for edge-enabled smart cities applications
Journal Article
Jan, M. A., Yeh, K., Tan, Z., & Wu, Y. (2021)
Blockchain for edge-enabled smart cities applications. Journal of Information Security and Applications, 61, 102937. https://doi.org/10.1016/j.jisa.2021.102937
The Internet of Things (IoT)-enabled devices are increasing at an exponential rate and share massive data generated in smart cities around the globe. The time-critical and del...
Evaluation of Ensemble Learning for Android Malware Family Identification
Journal Article
Wylie, J., Tan, Z., Al-Dubai, A., & Wang, J. (2020)
Evaluation of Ensemble Learning for Android Malware Family Identification. Journal of Guangzhou University (Natural Science Edition), 19(4), 28-41
Every Android malware sample generally belongs to a specific family that performs a similar set of actions and characteristics. Having the ability to effectively identify Andr...