Drawing from advanced mathematics, the technology employs a combination of bayesian models, artificial neural networks and k-mean clustering. Plurilock’s system builds user profiles, detects malicious behavior and stops intruders in real-time, securing the enterprise and solving key compliance challenges.
There is no configuration of rules or reliance on signatures for the system to operate. Instead, Plurilock ingests normal user behavior in the context of a company’s environment, and uses anomaly detection techniques to determine when behavior becomes abnormal. This fundamental shift from traditional technology that relies on rules and signatures to preconceive potential threats avoids the current arms race between attackers and defenders, as Plurilock can stop unknown unknowns.
