COMPOSITE BEHAVIORAL MODELING FOR IDENTITY THEFT DETECTION MIXTURE OF CLINICAL CONCEPTS

Abstract

In this work, we aim at building a bridge from coarse behavioral data to an effective,
quick-response, and robust behavioral model for online identity theft detection. We
concentrate on this issue in online social networks (OSNs) where users usually have
composite behavioral records, consisting of multidimensional low-quality data