Aditya Prasoon

Hybrid Federated Learning for Privacy-Preserving Intrusion Detection in Heterogeneous Network Environments

Centralized deep-learning intrusion detection systems (IDS) are accurate, but they scale badly and require raw traffic to be collected on one server, which creates privacy and communication problems. Federated learning (FL) avoids moving the data: clients train a shared model and exchange only updates. Its weakness is...