Decentralized Online Federated G-Network Learning for Lightweight Intrusion Detection. (arXiv:2306.13029v1 [cs.CR])

Cyberattacks are increasingly threatening networked systems, often with the
emergence of new types of unknown (zero-day) attacks and the rise of vulnerable
devices. While Machine Learning (ML)-based Intrusion Detection Systems (IDSs)
have been shown to be extremely promising in detecting these attacks, the need
to learn large amounts of labelled data often limits the applicability of
ML-based IDSs to cybersystems that only have access to private local data. To
address this issue, this paper proposes a novel Decentralized and Online …

attacks cyberattacks decentralized detection devices idss intrusion intrusion detection large learn machine machine learning network systems types vulnerable zero-day