Cyber-Attack Detection Framework for Connected Vehicles in V2X Networks Based on An Iterative UFIR Filter

Kai Jiang, Zhiyang Ju, Lingying Huang, Rong Su*

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Connected vehicles have great advantages in driving safety and energy efficiency under the support of vehicle-to-everything (V2X) networks, while they are also vulnerable to malicious cyber-attacks. To enhance the cyber security of connected vehicles, a cyber-attack detection framework is proposed based on multi-source information fusion specifically for the vehicle localization system. In this framework, an iterative unbiased finite impulse response (UFIR) filter is utilized to estimate the vehicle position with low computational load, based on the vehicle dynamics model and information from the inertial measurement system (IMU), GPS, and V2X networks. In addition, a discriminator module is developed to analyze the residuals between estimations and position information from different sources for cyber-attack detection. Finally, multiple simulation cases are implemented to validate the effectiveness of the proposed framework.

源语言英语
主期刊名2023 62nd IEEE Conference on Decision and Control, CDC 2023
出版商Institute of Electrical and Electronics Engineers Inc.
86-91
页数6
ISBN(电子版)9798350301243
DOI
出版状态已出版 - 2023
活动62nd IEEE Conference on Decision and Control, CDC 2023 - Singapore, 新加坡
期限: 13 12月 202315 12月 2023

出版系列

姓名Proceedings of the IEEE Conference on Decision and Control
ISSN(印刷版)0743-1546
ISSN(电子版)2576-2370

会议

会议62nd IEEE Conference on Decision and Control, CDC 2023
国家/地区新加坡
Singapore
时期13/12/2315/12/23

指纹

探究 'Cyber-Attack Detection Framework for Connected Vehicles in V2X Networks Based on An Iterative UFIR Filter' 的科研主题。它们共同构成独一无二的指纹。

引用此