Pilli Mounika

Fedagentshield: An Adaptive Federated Reinforcement Learning Framework for Privacy-Preserving Autonomous Cyber Defence

The proposed FedAgentShield framework is a scalable, adaptive, and privacy-preserving approach for next-generation autonomous cyber defence in distributed network environments and can enhance the quality of global policy updates by introducing an Adaptive Federated Policy Aggregation (AFPA) mechanism.