Federated Learning Inspired Low-Complexity Intrusion Detection and Classification Technique for SDN-Based Industrial CPS-Reference-Cited by-同舟云学术

Federated Learning Inspired Low-Complexity Intrusion Detection and Classification Technique for SDN-Based Industrial CPS

Author:

Zainudin Ahmad¹^ORCID,Akter Rubina²^ORCID,Kim Dong-Seong³^ORCID,Lee Jae-Min³^ORCID

Affiliation:

1. Department of Electronic Engineering, Kumoh National Institute of Technology, Gumi, South Korea

2. ICT Convergence Research Center, Kumoh National Institute of Technology, Gumi, Gyeongsangbuk, South Korea

3. Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, South Korea

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications

Link

Reference42 articles.

4. An interpretable federated learning-based network intrusion detection framework;dong;arXiv 2201 03134,2022

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2. EX-DFL: An Explainable Deep Federated-based Intrusion Detection System for Industrial IoT;2024 21st International Joint Conference on Computer Science and Software Engineering (JCSSE);2024-06-19