An insider threat prediction model

Authors:
Miltiadis Kandias;Alexios Mylonas;Nikos Virvilis;Marianthi Theoharidou;Dimitris Gritzalis
Affiliations:
Dept. of Informatics, Athens University of Economics and Business, Athens, Greece;Dept. of Informatics, Athens University of Economics and Business, Athens, Greece;Dept. of Informatics, Athens University of Economics and Business, Athens, Greece;Dept. of Informatics, Athens University of Economics and Business, Athens, Greece;Dept. of Informatics, Athens University of Economics and Business, Athens, Greece
Venue:
TrustBus'10 Proceedings of the 7th international conference on Trust, privacy and security in digital business
Year:
2010

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Abstract

Information systems face several security threats, some of which originate by insiders. This paper presents a novel, interdisciplinary insider threat prediction model. It combines approaches, techniques, and tools from computer science and psychology. It utilizes real time monitoring, capturing the user's technological trait in an information system and analyzing it for misbehavior. In parallel, the model is using data from psychometric tests, so as to assess for each user the predisposition to malicious acts and the stress level, which is an enabler for the user to overcome his moral inhibitions, under the condition that the collection of such data complies with the legal framework. The model combines the above mentioned information, categorizes users, and identifies those that require additional monitoring, as they can potentially be dangerous for the information system and the organization.