Robust Methods for Unsupervised PCA-based Anomaly Detection
نویسندگان
چکیده
The paper discusses the need for robust unsupervised anomaly detection. We focus on an approach that employs robust principal component analysis (PCA) to detect malicious behaviour. By using robust PCA, we can overcome the problem that we have to have enough anomaly–free data in the training phase of a detection system.
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