Tarik Taleb

The paper proposes a novel Federated Learning framework combined with Homomorphic Encryption and a dynamic agent selection scheme to enhance privacy and efficiency for anomaly detection in the Industrial Internet of Things (IIoT).

This paper proposes a semantic-aware multiple access scheme for efficient transmission of high-volume visual data among nearby vehicles in uplink-dominant 6G systems, reducing redundant transmissions and improving the proportion of users achieving high-fidelity reconstruction.