TY - GEN
T1 - A Data Transmission Behavior Simulation Platform for Security Supervision of Intelligent Connected Vehicles
AU - Wang, Weizhe
AU - Tian, Daxin
AU - Duan, Xuting
AU - Zhou, Jianshan
AU - Lang, Ping
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - For purposes such as safety and infotainment, intelligent connected vehicles (ICVs) require substantial data collection and transmission, which raises significant security concerns and regulatory efforts. Current development of supervision methods are hampered by the difficulty of accessing real traffic data and the lack of ground truth for abnormal data. Aimed at supplying abnormal test samples for the validation of supervision methods, this paper presents a platform that achieves the simulation of abnormal data transmission behaviors of ICVs. Our platform leverages autonomous driving simulator to create richly detailed urban traffic scenarios and integrate various common sensors. It supports prevalent vehicular communication standards such as SAE J2735 and GB/T 32960, ensuring that the generated traffic closely mirrors real-world conditions. By utilizing flexible scripts, our platform allows users to define and simulate specific abnormal transmission behaviors. Through case studies, we demonstrate its capability to simulate various abnormal transmission behaviors and provide valuable test data for the development of traffic analysis algorithms for ICV data security supervision.
AB - For purposes such as safety and infotainment, intelligent connected vehicles (ICVs) require substantial data collection and transmission, which raises significant security concerns and regulatory efforts. Current development of supervision methods are hampered by the difficulty of accessing real traffic data and the lack of ground truth for abnormal data. Aimed at supplying abnormal test samples for the validation of supervision methods, this paper presents a platform that achieves the simulation of abnormal data transmission behaviors of ICVs. Our platform leverages autonomous driving simulator to create richly detailed urban traffic scenarios and integrate various common sensors. It supports prevalent vehicular communication standards such as SAE J2735 and GB/T 32960, ensuring that the generated traffic closely mirrors real-world conditions. By utilizing flexible scripts, our platform allows users to define and simulate specific abnormal transmission behaviors. Through case studies, we demonstrate its capability to simulate various abnormal transmission behaviors and provide valuable test data for the development of traffic analysis algorithms for ICV data security supervision.
KW - Abnormal Data Transmission Behavior
KW - Data Security Supervision
KW - Intelligent Connected Vehicle
UR - https://www.scopus.com/pages/publications/105012034402
U2 - 10.1007/978-981-96-7441-1_19
DO - 10.1007/978-981-96-7441-1_19
M3 - 会议稿件
AN - SCOPUS:105012034402
SN - 9789819674404
T3 - Lecture Notes in Electrical Engineering
SP - 195
EP - 204
BT - Advances and Applications in SmartRail, Traffic, and Transportation Engineering - Proceedings of 2024 2nd International Conference on SmartRail, Traffic and Transportation Engineering, ICSTTE 2024
A2 - Jia, Limin
A2 - Wang, Yanhui
A2 - Easa, Said
PB - Springer Science and Business Media Deutschland GmbH
T2 - 2nd International Conference on SmartRail, Traffic and Transportation Engineering, ICSTTE 2024
Y2 - 25 October 2024 through 27 October 2024
ER -