A Distributed Mixture-of-Experts Framework for Cross-Dataset Intrusion Detection Using a Universal Flow Representation
Intrusion Detection Systems (IDS) trained on individual benchmark datasets often achieve high accuracy but fail to generalize across heterogeneous network environments due to domain shift. To address this challenge, this paper proposes U-Flow MoE-IDS, a distributed Mixture-of-Experts (MoE) framework for cross-dataset i...