Stealthy poisoning attacks on PCA-based anomaly detectors

Authors:
Benjamin I.P. Rubinstein;Blaine Nelson;Ling Huang;Anthony D. Joseph;Shing-hon Lau;Satish Rao;Nina Taft;J. D. Tygar
Affiliations:
University of California, Berkeley;University of California, Berkeley;Intel Research, Berkeley;University of California, Berkeley and Intel Research, Berkeley;University of California, Berkeley;University of California, Berkeley;Intel Research, Berkeley;University of California, Berkeley
Venue:
ACM SIGMETRICS Performance Evaluation Review
Year:
2009

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Abstract

We consider systems that use PCA-based detectors obtained from a comprehensive view of the network's traffic to identify anomalies in backbone networks. To assess these detectors' susceptibility to adversaries wishing to evade detection, we present and evaluate short-term and long-term data poisoning schemes that trade-off between poisoning duration and the volume of traffic injected for poisoning. Stealthy Boiling Frog attacks significantly reduce chaff volume,while only moderately increasing poisoning duration. ROC curves provide a comprehensive analysis of PCA-based detection on contaminated data, and show that even small attacks can undermine this otherwise successful anomaly detector.