Data pre-processing and analysis for insider threat detection - Ho, See Cheng (2019)
Insider threat is one of the most prominent concern in many companies. In this scenario, insiders are people with authorized access to sensitive information within the company. Insider threats are difficult to detect and thus, it is not enough to address simply through technical means alone. In order to help with the early detection of insider threats, emotional and social factors are to be considered. The project analyses emails, one of the most common mode of communication in most organizations and uses deep learning techniques to build user profile that includes sentiment and network information. These user profiles are updated at fixed interval and the anomalous users are viewed as potential insider threats.