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arXiv 2106.07541math.OCcs.SYeess.SY
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基于动态水印的编队网络机器人系统弹性控制

Resilient Control of Platooning Networked Robotic Systems via Dynamic Watermarking

Matthew Porter, Arnav Joshi, Sidhartha Dey, Qirui Wu, Pedro Hespanhol, Anil Aswani, Matthew Johnson-Roberson, Ram Vasudevan

摘要:

联网的机器人系统,如联网的车辆排,可以通过允许高速协调来提高运输网络的安全性和效率。为了实现这种协调,这些系统依赖于网络通信。这可能使他们容易受到网络攻击。虽然加密或专门设计的网络拓扑等安全方法可能会增加成功执行此类攻击的难度,但这些技术无法保证针对攻击者的安全通信。更麻烦的是,这些安全方法无法确保单个代理能够检测到更改特定消息内容的攻击。为了确保在这种攻击下的弹性行为,本文制定了一个网络化的线性时变版本的动态水印,其中每个代理生成并添加一个私人激励到其相应的机器人子系统的输入。本文证明,这种方法可以使网络机器人系统中的每个代理都能够检测网络攻击。通过改变车辆之间发送的测量值,本文说明了攻击者可以在一个队列中创建不稳定的行为。通过利用本文提出的动态水印方法,检测到的攻击,允许车队中的车辆优雅地降级到一个非通信控制策略,保持安全跨越各种场景。

英文摘要:

Networked robotic systems, such as connected vehicle platoons, can improve the safety and efficiency of transportation networks by allowing for high-speed coordination. To enable such coordination, these systems rely on networked communications. This can make them susceptible to cyber attacks. Though security methods such as encryption or specially designed network topologies can increase the difficulty of successfully executing such an attack, these techniques are unable to guarantee secure communication against an attacker. More troublingly, these security methods are unable to ensure that individual agents are able to detect attacks that alter the content of specific messages. To ensure resilient behavior under such attacks, this paper formulates a networked linear time-varying version of dynamic watermarking in which each agent generates and adds a private excitation to the input of its corresponding robotic subsystem. This paper demonstrates that such a method can enable each agent in a networked robotic system to detect cyber attacks. By altering measurements sent between vehicles, this paper illustrates that an attacker can create unstable behavior within a platoon. By utilizing the dynamic watermarking method proposed in this paper, the attack is detected, allowing the vehicles in the platoon to gracefully degrade to a non-communicative control strategy that maintains safety across a variety of scenarios.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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