Microsoft Technology Licensing, LLC

Xiang Wang

Bo Thiesson

Jack Wilson Stokes, Iii

Edward Wilkins Hardy

Jonathan Andreas Espenschied

Various technologies described herein pertain to detecting contextual anomalies in a behavioral network. Label propagation can be performed to construct contexts and assign respective context membership scores to users. Each context can be a respective subset of the users expected to have similar resource usages. The contexts can be constructed and the context membership scores can be assigned by combining behavioral information and contextual side information. The behavioral information can specify respective resource usages by the users within the behavioral network. Moreover, respective contextual anomaly scores for the users can be computed based on the respective context membership scores assigned to the users and the contextual side information. Further, the contextual anomalies can be detected from the contextual anomaly scores.

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Davis, CA, United States of America

Xiang Wang