Performing both security vulnerability assessment and configuration processes are heavily reliant on expert knowledge. This requirement often results in many systems being left insecure due to a lack of analysis expertise and access to specialist resources. It has long been known that a system's event log provides historical information depicting potential security threats, as well as recording configuration activities. In this paper, a novel technique is developed that can process security event logs on a computer that has been assessed and configured by a security professional, and autonomously establish causality amongst event log entries to learn performed configuration tasks. This extracted knowledge can then be exploited by non-professionals to plan steps that can improve the security of a previously unseen system.
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