The extensive use of distributed vehicle platoon controllers has resulted in
several benefits for transportation systems, such as increased traffic flow,
fuel efficiency, and decreased pollution. The rising reliance on interconnected
systems and communication networks, on the other hand, exposes these
controllers to potential cyber-attacks, which may compromise their safety and
functionality. This thesis aims to improve the security of distributed vehicle
platoon controllers by investigating attack scenarios and assessing their
influence on system performance. Various attack techniques, including
man-in-the-middle (MITM) and false data injection (FDI), are simulated using
Model Predictive Control (MPC) controller to identify vulnerabilities and
weaknesses of the platoon controller. Countermeasures are offered and tested,
that includes attack analysis and reinforced communication protocols using
Machine Learning techniques for detection. The findings emphasize the
significance of integrating security issues into their design and
implementation, which helps to construct safe and resilient distributed platoon
controllers.

本论文致力于通过研究攻击场景并评估其对系统性能的影响，来提高分布式车队控制器的安全性。使用模型预测控制 (MPC) 控制器模拟了各种攻击技术，包括中间人攻击和伪造数据注入，以识别车队控制器的漏洞和弱点。论文提供并测试了一些对策，其中包括使用机器学习技术进行攻击分析和加强通信协议。研究结果强调了将安全问题整合到设计和实施中的重要性，从而构建安全且具有弹性的分布式车队控制器。