K. R. Singh

Adaptive Intrusion Detection in WSNs Using Federated Deep Learning and Homomorphic Encryption

This research proposes a novel framework for anomaly detection in WSNs that leverages federated deep learning and prioritizes real-time adaptation and data privacy, and offers a promising path forward for securing WSNs by enabling distributed, privacy-preserving anomaly detection with real-time adaptation capabilities.