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Section: Publications & Resources

Publication: IEEE Transactions on Information Forensics and Security

To remove the contribution of specific data from the global model in federated learning, federated unlearning has recently emerged. Existing approaches face challenges such as reliance on full client

Section: Publications & Resources

Publication: IEEE Transactions on Information Forensics and Security

The coupling between radar and communication beams poses a central challenge to the beamforming design of covert integrated sensing and communication (ISAC) systems, as it distorts both the radar echo

Section: Publications & Resources

Publication: IEEE Transactions on Signal and Information Processing over Networks

This paper investigates the problem of fusion estimation by proposing both distributed and centralized fusion filtering algorithms, developed within the framework of the $\beta$-quaternion algebra. Th

Section: Publications & Resources

Publication: IEEE Transactions on Multimedia

Multi-object tracking is a crucial task in intelligent surveillance, yet it remains challenging in crowded environments due to severe occlusion, perspective distortion, and appearance similarity. To a

Section: Publications & Resources

Publication: IEEE Transactions on Multimedia

Multi-modal 3D object detection has exhibited significant progress in recent years. However, most existing methods can hardly scale to long-range scenarios due to their reliance on dense 3D features,

Section: Publications & Resources

Publication: IEEE Open Journal of Signal Processing

When a system operates under impulsive disturbances and conventional state estimation methods become ineffective, robust peak error reduction is required. In this paper, the error-to-error transfer fu

Section: Publications & Resources

Publication: IEEE Transactions on Information Forensics and Security

Private Hash Matching (PHM) enables the detection of harmful media in end-to-end encrypted communication by comparing user media hashes against a server-side set of known harmful hashes, without expos

Section: Publications & Resources

Publication: IEEE Transactions on Information Forensics and Security

Deep learning-based side-channel attack (DLSCA) has become the dominant paradigm for extracting sensitive information from hardware implementations due to its ability to learn discriminative features

Section: Publications & Resources

Publication: IEEE Transactions on Information Forensics and Security

The aim of a backdoor attack is to manipulate the behavior of a DNN under trigger-activated conditions by poisoning the dataset. Most backdoor detectors can be regarded as feature clustering methods a

Section: Publications & Resources

Publication: IEEE Transactions on Information Forensics and Security

Deep neural networks (DNNs) are vulnerable to backdoor/Trojan attacks, posing a severe threat to security-critical applications. In this paper, we investigate a scenario in which two different backdoo