Applying Genetic Algorithms for Minimization Analysis of Network Attack Graphs
Publish place: 11th Annual Conference of Computer Society of Iran
Publish Year: 1384
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
ACCSI11_199
تاریخ نمایه سازی: 5 آذر 1390
Abstract:
Each attack scenario is a sequence of exploits launched by an intruder for a particular goal such as access to a database, service disruption, and so on. The collection of possible attack scenarios in a computer network can be represented by a directed graph, which is called network attack graph. In this directed graph, each path from an initial node to a goal node corresponds to an attack scenario. The aim of minimization analysis of network attack graphs is to find a minimum critical set of exploits that must be prevented to guarantee no attack scenario is possible. In this paper, we propose a genetic algorithm for minimization analysis of network attack graphs. A special dynamic fitness function has been used to improve the overall performance of the proposed genetic algorithm. We also report the results of applying this genetic algorithm for minimization analysis of a sample network attack graph consisting of 164 attack scenarios. The results of experiments show that our proposed genetic algorithm can be successfully used for minimization analysis of network attack graphs.
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Authors
Mahdi Abadi
Department of Computer Engineering Tarbiat Modares University
Saeed Jalili
Department of Computer Engineering Tarbiat Modares University
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