Columbia University

Michael Prerau

Salvatore J Stolfo

Eleazar Eskin

Andrew Oliver Arnold

Leonid Portnoy

A method for unsupervised anomaly detection, which are algorithms that are designed to process unlabeled data. Data elements are mapped to a feature space which is typically a vector space. Anomalies are detected by determining which points lies in sparse regions of the feature space. Two feature maps are used for mapping data elements to a feature apace. A first map is a data-dependent normalization feature map which we apply to network connections. A second feature map is a spectrum kernel which we apply to system call traces.

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Chestnut Hill, MA, United States of America

Michael Prerau