An Assessment of Data Analytics Techniques for Insider Threat Programs

A wide array of data analytics methods, tools, and techniques exist to improve the detection and mitigation of insider threats – trusted employees who seek to steal an organization’s data or intellectual property or to harm an organization or its staff. Determining which data analytics methods and software tools are best for an organization, however, depends on the quality and comprehensiveness of data, the clarity of rules, the organization’s risk tolerance, and other factors.

This paper presents a framework which plots the continuum of data analytics techniques used to solve specific insider threat problems. Decision-makers and insider threat program managers in both government and industry can leverage this framework to evaluate the merits of different analytic techniques and then choose or develop tools to address their most pressing needs.

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