Iterative Selection of Cost-Effective Countermeasures for Intelligent Threat Agents

Abstract

We describe the tools of the Haruspex suite to manage the risk due to intelligent agents. The suite applies a Monte Carlo method and it return a statistical samples on the attacks these agents implement. Some tools of the suite analyzes these samples to select the countermeasures to deploy. The tools work in an iterative way that alternates the selection of countermeasures and the application of the Monte Carlo method. This takes into account that an intelligent agent may select distinct attacks to replace those affected by the countermeasures. Lastly, we apply the tools to three industrial control systems.