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Most of the existing solutions to enterprise threat management are preventiveapproaches prescribing means to prevent policy violations with varying degreesof success. In this paper we consider the complementary scenario where a numberof security violations have already occurred, or security threats, orvulnerabilities have been reported and a security administrator needs togenerate optimal response to these security events. We present a principledapproach to study and model the human expertise in responding to the emergentthreats owing to these security events. A recursive Partial Least Squares basedadaptive learning model is defined using a factorial analysis of the securityevents together with a method for estimating the effect of global contextdependent semantic information used by the security administrators. Presentedmodel is theoretically optimal and operationally recursive in nature to dealwith the set of security events being generated continuously. We discuss theunderlying challenges and ways in which the model could be operationalized incentralized versus decentralized, and real-time versus batch processing modes.

A Recursive PLS (Partial Least Squares) based Approach for Enterprise Threat Management