Can You Trust Autonomous Vehicles : Contactless Attacks against Sensors of Self-driving Vehicle
Can You Trust Autonomous Vehicles : Contactless Attacks against Sensors of Self-driving Vehicle
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发表时间：
2016
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通讯作者：
Chen Yan
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作者：
Chen Yan
为了改善道路安全和驾驶体验，最近出现了自动驾驶汽车，它们可以在没有人为干预的情况下感知周围环境并进行导航。虽然这些汽车有前途，并证明了安全功能，但在它们被广泛采用之前，必须检查它们的可靠性。与传统的网络安全不同，自动驾驶汽车在很大程度上依赖于其对周围环境的感知能力来做出驾驶决策，这会带来来自传感器的安全风险。因此，在本文中，我们研究了自动驾驶汽车传感器的安全性，并调查了汽车的“眼睛”的可信度。我们的工作研究传感器，其测量用于指导驾驶，即，毫米波雷达超声波传感器前视摄像头特别是，我们提出了对这些传感器的非接触式攻击，并展示了我们在实验室和特斯拉Model S汽车上收集的结果。我们证明，使用现成的硬件，我们能够执行干扰和欺骗攻击，这导致特斯拉的失明和故障，所有这些都可能导致撞车并损害自动驾驶汽车的安全。为了缓解这些问题，我们提出了软件和硬件对策，这将提高传感器对这些攻击的弹性。
To improve road safety and driving experiences, autonomous vehicles have emerged recently, and they can sense their surroundings and navigate without human intervention. Although promising and proving safety features, the trustworthiness of these cars has to be examined before they can be widely adopted on the road. Unlike traditional network security, autonomous vehicles rely heavily on their sensory ability of their surroundings to make driving decision, which incurs a security risk from sensors. Thus, in this paper we examine the security of the sensors of autonomous vehicles, and investigate the trustworthiness of the ‘eyes’ of the cars. Our work investigates sensors whose measurements are used to guide driving, i.e., millimeter-wave radars, ultrasonic sensors, forward-looking cameras. In particular, we present contactless attacks on these sensors and show our results collected both in the lab and outdoors on a Tesla Model S automobile. We show that using o↵-the-shelf hardware, we are able to perform jamming and spoofing attacks, which caused the Tesla’s blindness and malfunction, all of which could potentially lead to crashes and impair the safety of self-driving cars. To alleviate the issues, we propose software and hardware countermeasures that will improve sensor resilience against these attacks.