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InfoResearchPeer-reviewed
Ano2Rule: Rule-Based Global Interpretation for Unsupervised Anomaly Detection in Security
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Summary
Ano2Rule is a rule-based method that makes unsupervised anomaly detection models interpretable for security use. It decomposes normal data into compositional distributions using an unsupervised Interior Clustering Tree, then applies Compositional Boundary Exploration to infer the original model's decision boundary on each part. Experiments on network intrusion detection and IoT security datasets reported high fidelity to the original model's predictions.