Multi-Agent Locally Trained Progressive Instance Selected Assisted Federated Learning Architecture for Intrusion Detection in Industrial-IoT

Divyashree R; Dr. Sumati Ramakrishna Gowda

doi:10.32628/CSEIT24106190

Authors

Divyashree R Department of Computer Science, Karnataka State Open University, Mysore, Karnataka, India Author
Dr. Sumati Ramakrishna Gowda Department of Computer Science, Karnataka State Open University, Mysore, Karnataka, India Author

DOI:

https://doi.org/10.32628/CSEIT24106190

Keywords:

Industrial-IoT, Federated learning model, Multi-type network intrusion detection system, Intrusion Detection

Abstract

In this work the focus is made on designing and developing a robust federated learning model (FLM) and architecture for multi-type network intrusion detection system (MT-NIDS) for IIoT applications. Unlike traditional intrusion detection systems, where the key focus is made on detecting and classifying single type of intrusion or attack condition, this research targets to perform multi-type network intrusion detection. This as a result can contribute a fit-to-all NIDS solution for IIoT environment.

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