基于自适应分布式卡尔曼滤波的网联车GPS虚假注入攻击检测OA
Detection of GPS spoofing attacks on connected vehicles based on adaptive distributed Kalman filtering
针对网联车GPS信号可能遭受虚假注入攻击的问题,本文提出一种基于自适应分布式卡尔曼滤波DKF的攻击检测策略.首先,构建GPS信号虚假注入攻击下的网联车队列系统不确定动态模型,并提出一种自适应DKF算法,以解决网联车行驶过程中噪声统计特性未知的问题;其次,设计了一种基于自适应DKF状态残差的卡方检测方法,实现对GPS信号虚假注入攻击的检测;最后,通过实验仿真验证所提检测方法的有效性.
To address the issue of potential spoofing attacks on GPS signals in connected vehicles,this paper proposes an attack detection strategy based on an adaptive distributed Kalman filtering(DKF).Firstly,an uncertain dynamical model of a connected vehicle platooning system subject to the GPS spoofing attack is derived,and then an adaptive DKF algorithm is proposed to solve the problem of unknown noise statistical properties of the connected vehicles in driving.Secondly,a chi-square detection method based on the state residuals of the DKF is designed to detect GPS spoofing attacks.Finally,the effectiveness of the proposed detection method is verified through experimental simulations.
宋秀兰;梅正远;朱俊威
浙江工业大学信息工程学院,浙江 杭州 310023浙江工业大学信息工程学院,浙江 杭州 310023浙江工业大学信息工程学院,浙江 杭州 310023
网联车车辆安全虚假注入攻击入侵检测卡尔曼滤波
connected vehiclesvehicle safetyspoofing injection attackintrusion detectionKalman filter
《控制理论与应用》 2026 (1)
159-168,10
国家自然科学基金项目(62273307),浙江省公益性技术应用研究项目(LGF22F030013)资助.Supported by the National Natural Science Foundation of China(62273307)and the Public Welfare Technology Application Research Project of Zhe-jiang Province(LGF22F030013).
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