Anomalous Behavior Detection in Mobile Network

Abstract

New security threats emerge against mobile devices as the devices’ computing power and storage capabilities evolve. Preventive mechanisms like authentication, encryption alone are not sufficient to provide adequate security for a system. There is a definite need for Anomaly detection systems that will improve security on the mobile phone. In this work, we propose User Group Partition Algorithm and Behavior Pattern Matching Algorithm to extract anomalous calls from mobile call detail records effectively.