The demands of Counter-Insider Threat (C-InT) assessment to fully address the insider threat analysis problem exceeds currently fielded solutions and overwhelm the cognitive limitations of C-InT professionals. In contrast to current practice that is largely reactive, a continuous intelligence approach with an advanced behavioral analytic is needed to achieve a comprehensive, proactive C-InT program that can handle the data analysis demands and decision support for C-InT professionals. Analysis of behavioral and technical data in a predictive, unified real-time platform (URP) will deliver a whole person C-InT program that monitors and detects potential insider risks so that threat mitigation efforts can be applied to help detect or avoid incidents.
Intelligence analysts and decision makers, and by extension the enterprise, are largely behind the curve when it comes to implementing effective predictive intelligence solutions. This is due to the ever-expanding flow of data and the limitations of current IT and analytic systems. Analysts are simply overwhelmed, resulting in unquantifiable risk exposure and lost opportunity for the enterprise.