A Privacy-Preserving Intrusion Detection System for IoT Networks Using Federated Learning
The experimental results demonstrate that the proposed framework not only maintains competitive detection performance and data privacy but also reduces computational and memory requirements, supporting its suitability as an effective and lightweight IDS for resource-constrained IoT environments.