Enhancing Industrial Control Network Security Through Vulnerability Detection and Attack Graph Analysis

Author:

Liao Yan

Abstract

Insufficient communication attack defense capabilities within industrial control networks is a serious problem that is addressed in this study. The author proposes a methodology that focuses on creating attack graphs to ease security and vulnerability studies in industrial control network systems in order to address this issue. The article provides thorough construction guidance and techniques for attack graphs, which are used for penetration testing and vulnerability analysis of networks for industrial control systems. On the created attack graph, experimental evaluations utilizing the ``earthquake net'' virus were carried out. The findings point to four main attack routes where the ``Zhenwang'' virus is most likely going to attack and cause the most damage. With a loss value of 12.2 and an attack success chance of 0.096, the first path involves cumulative attack stages. The second path consists of cumulative attack steps, with a loss value of 10.2 and an attack success probability of 0.072. The third path encompasses cumulative attack steps, with a loss value of 16.6 and an attack success probability of 0.063. The fourth path comprises cumulative attack steps, with a loss value of 18.6 and an attack success probability of 0.084.

Publisher

Scalable Computing: Practice and Experience

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