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Bo-Yu Liu

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Jul 2026

GIC-IDS: A Unified Graph Intrusion Detection Framework with Information Bottleneck and Contrastive Learning

GIC-IDS is proposed, a unified intrusion detection framework that integrates graph structure learning, information bottleneck, and contrastive learning that consistently outperforms representative baseline methods in terms of detection accuracy, robustness, and generalization capability.

Ya Guo, Junyi Wang, Boyu Liu et al. · 0 citations

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