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HyperLAC: Hypergraph-based Large-scale Alert Classification with spatial-temporal context enhancement
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AI
DOI：10.1016/j.knosys.2025.114712.png)
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Abstract
En 中文
• We propose HyperLAC, a hypergraph-based large-scale alerts classification with spatialtemporal context enhancement. • We introduce AIHC, an efficient hypergraph clustering algorithm for security event extraction. • We demonstrate a feature-centric approach enables lightweight models to achieve state of-the-art accuracy. • Experiments on large-scale, real-world datasets validate our method’s effectiveness and robustness.
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