The “3D-IDS: Doubly Disentangled Dynamic Intrusion Detection” study developed by a team from the Beijing University of Posts and Telecommunications presents a novel method that aims to enhance network intrusion detection systems (NIDS). This research is specifically targeted at improving the system’s ability to detect both known and unknown cyber threats. The method utilizes a double-feature disentanglement scheme that enhances the detection and differentiation of attacks, thereby addressing the problem of entangled distributions of flow features.
Publication date: 2 Jul, 2023
Project Page: N/A
Paper: https://arxiv.org/pdf/2307.11079.pdf
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