Study on cybersecurity attack-defense visualization method based on intelligent connected vehicle

• Main Authors: Wang Yafei, Han Shengqiang, Zhang Nan, Hu Peng
• Format: Article
• Language: English
• Published: EDP Sciences 2021-01-01
• Series: E3S Web of Conferences
• Subjects: intelligent connected vehicle; cybersecurity; attack-defense; visualization
• Online Access: https://www.e3s-conferences.org/articles/e3sconf/pdf/2021/44/e3sconf_vesep2020_01010.pdf

Attack test and defense verification are important ways to effectively evaluate the cybersecurity performance of Intelligent Connected Vehicle (ICV). This paper investigates the problem of attack-defense visualization in ICV cybersecurity. For the purpose of promoting cybersecurity research capabilities, a novel Cybersecurity Attack-Defense Visualization method based on Intelligent Connected Vehicle (CADV-ICV) is proposed. In this scheme, an Attack-Defense Game model (ADG) is designed so that the logical relationship between the attack and defense can be studied through a system architecture. Then, the CADV-ICV method is implemented through three layers that are hardware layer, software layer and visualization layer. Finally, through an Intelligent Connected Vehicle, two TV monitors, a computer and a server, a real experimental environment is built to test the CADV-ICV method. The experimental results show that CADV-ICV can realize the visual display of attack-defense process, attack messages, defense state, real-time message monitoring, and attack-defense principle for 10 car’s components.