论文标题
SOK：从系统的角度重新考虑传感器欺骗机器人车辆的攻击
SoK: Rethinking Sensor Spoofing Attacks against Robotic Vehicles from a Systematic View
论文作者
论文摘要
在过去的几年中，机器人车（RV）在广受欢迎。同时，它们也被证明容易受到传感器欺骗攻击的攻击。尽管大量的研究工作已经提出了各种攻击，但一些关键问题仍未得到解答：这些现有作品是否足够完整以涵盖所有传感器欺骗威胁？如果没有，没有探索多少次攻击，认识到它们有多困难？本文通过全面地系统化传感器欺骗对RV的攻击的知识来回答上述问题。我们的贡献是三倍。 （1）我们在RV系统管道中识别七个常见的攻击路径。我们从Spoofer财产，操作，受害者特征和攻击目标的角度对现有的欺骗攻击进行了分类和评估。基于这种系统化，我们确定了有关欺骗攻击设计的4个有趣的见解。 （2）我们提出了一个新型的动作流模型，以系统地描述机器人功能执行和未开发的传感器欺骗威胁。使用此模型，我们成功发现了103个欺骗攻击向量，其中26个已通过先前的作品进行了验证，而从未考虑过77次攻击。 （3）我们设计了两种新型攻击方法，以验证新发现的欺骗攻击载体的可行性。
Robotic Vehicles (RVs) have gained great popularity over the past few years. Meanwhile, they are also demonstrated to be vulnerable to sensor spoofing attacks. Although a wealth of research works have presented various attacks, some key questions remain unanswered: are these existing works complete enough to cover all the sensor spoofing threats? If not, how many attacks are not explored, and how difficult is it to realize them? This paper answers the above questions by comprehensively systematizing the knowledge of sensor spoofing attacks against RVs. Our contributions are threefold. (1) We identify seven common attack paths in an RV system pipeline. We categorize and assess existing spoofing attacks from the perspectives of spoofer property, operation, victim characteristic and attack goal. Based on this systematization, we identify 4 interesting insights about spoofing attack designs. (2) We propose a novel action flow model to systematically describe robotic function executions and unexplored sensor spoofing threats. With this model, we successfully discover 103 spoofing attack vectors, 26 of which have been verified by prior works, while 77 attacks are never considered. (3) We design two novel attack methodologies to verify the feasibility of newly discovered spoofing attack vectors.
