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 under Paillier Homomorphic Encryption

摘要:

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距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。

Abstract:

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 the network, cyber attacks pose a great threat to the security of connected vehicle systems. To address the problem that the traditional scheme is more cumbersome and the ciphertext key can still be tampered with when transmitting data at the same time, the Paillier homomorphic encryption algorithm is used to encrypt the acceleration and transmit only the ciphertext. In order to achieve control objectives, an integrated tracking signal is designed and the ciphertext multiplication operation is designed based on the homomorphism of the Paillier algorithm, so that the acceleration ciphertext can be used di-rectly to construct the tracking signal from the vehicle without decryption. The tracking signal is combined with distributed model predictive control (MPC), and linear matrix inequalities are used to transform the optimization problem of the control strategy to solve for the optimal control inputs to ensure the safe co-movement of the vehicle queue. The performance metrics of the control system and the effectiveness of Paillier homomorphic encryption are verified by MATLAB simulation.