Sawera Kanwal

Abstract The fast growth of Internet of Things (IoT) systems has made them very susceptible to advanced cyber-attacks, and an intelligent and privacy-sustainable intrusion detection system is required. Conventional centralized intrusion detection frameworks have the drawbacks of data privacy threats, scale constraints, and a single point of failure, and conventional federated learning still faces the threat of malicious client membership and a lack of trust during model aggregation.