Reliable Federated Learning Assisted Intrusion Detection Using SSL/TLS

This article details a federated learning based intrusion detection architecture that reinforces confidentiality through SSL and TLS channels. The approach reduces communication overhead, defends against stealthy false data injection attacks, and demonstrates strong performance on datasets such as CIFAR10 and MNIST. The framework advances privacy aware threat mitigation for IoT and edge networks.