Enhancing Intrusion Detection Through Federated Learning With Enhanced Ghost_BiNet and Homomorphic Encryption

Enhancing Intrusion Detection Through Federated Learning With Enhanced Ghost_BiNet and Homomorphic Encryption

Intrusion detection is essential for safeguarding computer systems and networks against unauthorized access, malicious activities, and security breaches. Its application domains include network security, information security, and cybersecurity across various sectors such as finance, healthcare, gove...

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Bibliographic Details
Main Authors: Om Kumar ChandraUmakantham, Sudhakaran Gajendran, Suguna Marappan
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Federated learning
intrusion detection
hybrid deep learning
homomorphic encryption
enhanced Ghost_BiNet
privacy
Online Access:https://ieeexplore.ieee.org/document/10422789/

Internet

https://ieeexplore.ieee.org/document/10422789/

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