Poster: CMA-FL: Cognitive Multi-Agent Federated Learning for Resource-Aware Drone Communication Attack Detection
CMA-FL is proposed, a cognitive multi-agent assisted FL framework for resource-aware intrusion detection in drone communication networks that achieves 99.6% accuracy with 0.99 precision, recall, and F1-score and reduces response time by more than 80% relative to the evaluated FL, edge-cloud, and cloud-only alternatives...
Pronaya Bhattacharya, A. Mukherjee, Somnath Bera et al.
· Proceedings of the 7th Inter... · 0 citations