Dynamical System approach to insider threat detection

Abstract

Insider attacks have the potential to inflict severe damage to an organizations reputation, intellectual property and financial assets. The primary difference between the external intrusions and the insider intrusions is that an insider wields power of knowledge about the information system resources, their environment, policies. We present an approach to detecting abnormal behavior of an insider by applying Dynamical System Theory to the insiders computer usage pattern. This is because abnormal system usage pattern is one of the necessary precursors to actual execution of an attack. A base profile of system usage pattern for an insider is created via applying dynamical system theory measures. A continuous monitoring of the insiders system usage and its comparison with this base profile is performed to identify considerable deviations. A sample system usage in terms of application system calls is collected, analyzed, and graphical results of the analysis are presented. Our results indicate that dynamical system theory has the potential of detecting suspicious insider behavior occurring prior to the actual attack execution.