Insider Threat Detection Using Natural Language Processing and Personality Profiles

Abstract

This work represents an interdisciplinary effort to proactively identify insider threats, using natural language processing and personality profiles. Profiles were developed for the relevant insider threat types using the five-factor model of personality and were used in a proof-of-concept detection system. The system employs a third-party cloud service that uses natural language processing to analyze personality profiles based on personal content. In the end, an assessment was made over the feasibility of the system using a public dataset.