An ACO Based Approach for Detection of an Optimal Attack Path in a Dynamic Environment

Abstract

Abstract Attack graph is a tool to analyze multi-stage, multi-host attack scenarios in a network. Each attack scenario is depicted by an attack path which is essentially a series of exploits with a severity score that presents a comparative desirability of a particular network service. In an attack graph with a large number of attack paths, it may not be feasible for the administrator to plug all the vulnerabilities. Moreover, in a dynamic environment where the severity of an exploit changes with time, a framework is required that detects an optimal attack path or most favored path from a given attack graph in an environment. This paper proposes a framework for finding out an optimal attack path using Ant Colony Optimization (ACO) technique under a dynamic environment. Given an attack graph and the severity scores of the exploits, an optimal attack path is detected using customized ACO algorithms. A case study has been presented to demonstrate the efficacy of the proposed methodology.KeywordsDynamic EnvironmentTime SlicePheromone TrailTest NetworkAttack ScenarioThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.