A Secure and Privacy-Preserving Federated Learning-Based Intrusion Detection System for SDN Networks Using Homomorphic Encryption

Software-Defined Networking (SDN) has revolutionized network management by separating the control and data planes; nevertheless, this architectural centralization introduces significant security vulnerabilities. To mitigate these risks, Intrusion Detection Systems (IDSs) are widely deployed in SDN e...

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書誌詳細

出版年:	IEEE Access
主要な著者:	S. M. Shamim, Yuta Kodera, Md. Arshad Ali, Yasuyuki Nogami
フォーマット:	論文
言語:	英語
出版事項:	IEEE 2026-01-01
主題:	Software defined networks federated learning homomorphic encryption intrusion detection system machine learning
オンライン･アクセス:	https://ieeexplore.ieee.org/document/11511721/