Using Internet Activity Profiling for Insider-threat Detection

The insider-threat problem continues to be a major risk to both public and private sectors, where those people who have privileged knowledge and access choose to abuse this in some way to cause harm towards their organisation. To combat against this, organisations are beginning to invest heavily in deterrence monitoring tools to observe employees’ activity, such as computer access, Internet browsing, and email communications. Whilst such tools may provide some way towards detecting attacks afterwards, what may be more useful is preventative monitoring, where user characteristics and behaviours inform about the possibility of an attack before it happens. Psychological research advocates that the behaviour and preference of a person can be explained to a great extent by psychological constructs called personality traits, which could then possibly indicate the likelihood of an individual being a potential insider threat. By considering how browsing content relates to psychological constructs (such as OCEAN), and how an individual’s browsing behaviour deviates over time, potential insider-threats could be uncovered before significant damage is caused. The main contribution in this paper is to explore how Internet browsing activity could be used to predict the individual’s psychological characteristics in order to detect potential insider-threats. Our results demonstrate that predictive assessment can be made between the content available on a website, and the associated personality traits, which could greatly improve the prospects of preventing insider attacks.