Attack Graph Generation and Visualization for Industrial Control Network
Yanli Feng, Gongliang Sun, Zhiyao Liu, Chenrui Wu, Xiaoyang Zhu, Zibo Wang, Bailing Wang · 2020
Attack graph is an effective way to analyze the vulnerabilities for industrial control networks. We develop a vulnerability correlation method and a practical visualization technology for industrial control network. First of all, we give a complete attack graph analysis for industrial control network, which focuses on network model and vulnerability context. Particularly, a practical attack graph algorithm is proposed, including preparing environments and vulnerability classification and correlation. Finally, we implement a three-dimensional interactive attack graph visualization tool. The experimental results show validation and verification of the proposed method.