Security analytics company Interset wants to change the way IT pros think about security and bring the concept of reputation-based security scoring to a broader market, with the Interset Behavioral Analytics Engine. The offering can be best described as an extensible platform that incorporates machine learning that identifies security exceptions. In other words, the product ingests massive amounts of activity data and then uses AI to normalize the activity associated with the data. The technology, an extension of big data analytics, applies self-learning algorithms to build what can be referred to as “Access Stories,” which are conceptualized reports that illustrate access behaviors and then place those behaviors in easy-to-understand contexts. Interset has demonstrated an uncanny ability to detect threats in real time, which gain additional meaning by being associated with context and reputation scores, enabling administrators to take action before those threats become serious data loss problems. Using access data as the glue to meld activity, users, applications and devices brings contextual security to the enterprise, while easing forensics and improving identity management.

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