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Anomalies in computer usage data may be indicative of insider threats. Distinguishing actual malicious activities from unusual but justifiable activities requires not only a sophisticated anomaly detection system but also the expertise of human analysts with access to additional data sources. Because any anomaly detection system for extremely rare events will generate many false positives, human analysts...
This paper reports results from a set of experiments that evaluate an insider threat detection prototype on its ability to detect scenarios that have not previously been seen or contemplated by the developers of the system. We show the ability to detect a large variety of insider threat scenario instances imbedded in real data with no prior knowledge of what scenarios are present or when they occur...
This paper reports the first set of results from a comprehensive set of experiments to detect realistic insider threat instances in a real corporate database of computer usage activity. It focuses on the application of domain knowledge to provide starting points for further analysis. Domain knowledge is applied (1) to select appropriate features for use by structural anomaly detection algorithms,...
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