A Privacy Preserving Context-Aware Insider Threat Prediction and Prevention Model Predicated on the Components of the Fraud Diamond

This paper presents a novel, interdisciplinary insider threat prediction and prevention model which combines several approaches, techniques and tools from computer science, criminology and psychology. It is based on the fraud diamond which comprises four components: pressure (i.e. motive), opportunity, capability and rationalisation. In general, it has been found that a criminal must have the motive and opportunity to commit a crime. However, the criminal must also have the capability to commit crime particularly in the cybercrime domain. Furthermore, criminals tend to rationalise (i.e. excuse) their crimes. The model presented here involves leveraging the fraud diamond to predict and prevent insider threats. Typically insider threat prediction and prevention models tend to overlook the privacy concerns of insiders. Hence the deployment of the model involves gathering information about the insider's possible intent within a privacy-preserving context. This will help to identify high risk insider threats while balancing privacy concerns.