Date of Award


Document Type


Degree Name

Master of Science


Department of Electrical and Computer Engineering

First Advisor

Robert F. Mills, PhD


The advancement of technology and reliance on information systems have fostered an environment of sharing and trust. The rapid growth and dependence on these systems, however, creates an increased risk associated with the insider threat. The insider threat is one of the most challenging problems facing the security of information systems because the insider already has capabilities within the system. Despite research efforts to prevent and detect insiders, organizations remain susceptible to this threat because of inadequate security policies and a willingness of some individuals to betray their organization. To investigate these issues, a formal security model and risk analysis framework are used to systematically analyze this threat and develop effective mitigation strategies. This research extends the Schematic Protection Model to produce the first comprehensive security model capable of analyzing the safety of a system against the insider threat. The model is used to determine vulnerabilities in security policies and system implementation. Through analysis, mitigation strategies that effectively reduce the threat are identified. Furthermore, an action-based taxonomy that expresses the insider threat through measurable and definable actions is presented. A risk analysis framework is also developed that identifies individuals within an organization that display characteristics indicative of a malicious insider. The framework uses a multidisciplinary process by combining behavior and technical attributes to produce a single threat level for each individual within the organization. Statistical analysis using the t-distribution and prediction interval on the threat levels reveal those individuals that are a potential threat to the organization. The effectiveness of the framework is illustrated using the case study of Robert Hanssen, demonstrating the process would likely have identified him as an insider threat.

AFIT Designator