Whether we’re talking about business or government, modern work practices require growing numbers of individuals to have access to critical organizational information. It’s a byproduct of this reality that insider threats, whether malicious or unintentional, are more frequently leading to severe and costly damages at large organizations. It takes only a quick news search to see that recent insider cases have led to the loss of export-controlled warfighting capabilities, the exposure of sensitive information, and even to attacks on U.S. military personnel.
Insider threat programs are a natural and necessary response to these circumstances. They enable faster detection of potential risks and the ability to proactively respond to threats. But the growing complexity of risk behaviors and the large volume of data mining now required to effectively monitor them demands new and innovative technical approaches to the job.
By adding advanced analytics and analysis to your organization’s insider threat detection and response toolkit, you can empower your security team to substantially improve monitoring, better protect assets, and more rapidly respond to risks and incidents. Booz Allen has helped advance insider threat tools and programs for government and commercial clients based in Washington, DC; Huntsville, AL; Chicago, IL; New York, NY; and elsewhere. We accomplish this work using machine learning (ML) algorithms in conjunction with the most recent major innovation in big data management: data mesh architecture.