Anomalous Behavior Detection in Mobile Network

New security threats emerge against mobiledevices as the devices’ computing power and storagecapabilities evolve. Preventive mechanisms likeauthentication, encryption alone are not sufficient toprovide adequate security for a system. There is adefinite need for Anomaly detection systems that willimprove security on the mobile phone. In this work, wepropose User Group Partition Algorithm and BehaviorPattern Matching Algorithm to extract anomalous callsfrom mobile call detail records effectively