Paillier同态加密下车辆协同自适应预测巡航控制

Cooperative Adaptive Predictive Cruise Control for Vehicles with Paillier Homomorphic Encryption

车辆协同式自适应巡航控制(CACC)以其高效便捷的特点成为智能交通系统的研究热点,但随着车辆接入网络,网络攻击对车联网系统的安全性造成了很大威胁;针对传统方案较繁琐、密文密钥同时传输数据仍可能被篡改的问题,采用Paillier同态加密算法对加速度进行加密,仅传输密文;针对控制目标设计一综合跟踪信号,并基于Paillier算法的同态性设计密文数乘运算,使加速度密文无须解密而直接用于自车构建跟踪信号;将跟踪信号与分布式模型预测控制(MPC)结合,采用线性矩阵不等式对控制策略的优化问题进行转化,求解最优控制输入,保证车辆队列的安全协同行驶;经Matlab仿真验证了控制系统的性能指标以及Paillier同态加密的有效性。

Vehicle cooperative adaptive cruise control(CACC) has become a research hotspot for intelligent transportation systems with its efficient and convenient features,but with the access of vehicles to networks,cyber attacks cause a significant threat to the security of connected vehicle systems.To address the problems of complex traditional scheme ciphertext key to be simultaneously changed during transmitting data,the Paillier homomorphic encryption algorithm is used to encrypt the acceleration,only transmitting the ciphertext.To achieve the control object,this paper designs an integrated tracking signal and ciphertext multiplication operation based on the homomorphism of the Paillier algorithm,so that the acceleration ciphertext directly constructs the tracking signal from the vehicle without decryption.The tracking signal is combined with the distributed model predictive control(MPC),the linear matrix inequalities are used to transform the optimization problem of the control strategy,solve the optimal control inputs,and ensure the safety cooperative movement of the vehicle queue.The performance of the control system and effectiveness of the Paillier homomorphic encryption are verified by MATLAB simulation.