This thesis focuses on developing a system for insider threat detection using machine learning.
An insider threat is a malicious threat that comes from trusted actors of the organization with privileged knowledge. These actors could exploit their position and steal valuable corporate property. According to the Verizon data breach report from 2017, 25% of all breaches are coming from insider actors. Despite that it is a major problem, corporations often do not invest in the detection of Insider Threats, as most of them do not know of the potential financial losses. According to an Insider Threat survey from SANS Institute, 45% of respondents did not know the potential for financial losses associated with an insider incident, while another 33% were unable to place a value on the losses.