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Found 3 papers, 3 papers with code
threaTrace: Detecting and Tracing Host-based Threats in Node Level Through Provenance Graph Learning
Recent studies propose leveraging the rich contextual information in data provenance to detect threats in a host.
DeepAID: Interpreting and Improving Deep Learning-based Anomaly Detection in Security Applications
Experimental results show that DeepAID can provide high-quality interpretations for unsupervised DL models while meeting the special requirements of security domains.
Evaluating and Improving Adversarial Robustness of Machine Learning-Based Network Intrusion Detectors
Many adversarial attacks have been proposed to evaluate the robustness of ML-based NIDSs.
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