机器人车辆安全检测的网络物理不一致漏洞识别

Hongjun Choi, Sayali Kate, Yousra Aafer, X. Zhang, Dongyan Xu
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引用次数: 13

摘要

我们提出了一种新的机器人车辆(RVs)漏洞类型,称为网络物理不一致性。这些漏洞的目标是rv中的安全检查(例如,崩溃检测)。可以通过设置恶意环境条件来利用它们,例如在RV的轨道上放置具有一定重量和一定角度的障碍物。一旦被利用,安全检查可能无法报告真实的物理事故或报告假警报(而RV仍然正常运行)。这两种情况都可能导致危及生命的后果。这些漏洞的根本原因是,现有的安全检查大多使用通用编程语言实现的简单范围检查,这些检查无法描述复杂而微妙的物理世界。我们开发了一种新技术,该技术需要程序分析、车辆建模和基于搜索的测试来相互作用,以识别此类漏洞。我们对四旋翼机、漫游者、固定翼飞机等4种真实控制软件和8种飞行器进行了实验,发现了10个真实漏洞。我们的技术没有误报,因为它只在可以生成漏洞时报告。
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Cyber-Physical Inconsistency Vulnerability Identification for Safety Checks in Robotic Vehicles
We propose a new type of vulnerability for Robotic Vehicles (RVs), called Cyber-Physical Inconsistency. These vulnerabilities target safety checks in RVs (e.g., crash detection). They can be exploited by setting up malicious environment conditions such as placing an obstacle with a certain weight and a certain angle in the RV's trajectory. Once exploited, the safety checks may fail to report real physical accidents or report false alarms (while the RV is still operating normally). Both situations could lead to life-threatening consequences. The root cause of such vulnerabilities is that existing safety checks are mostly using simple range checks implemented in general-purpose programming languages, which are incapable of describing the complex and delicate physical world. We develop a novel technique that requires the interplay of program analysis, vehicle modeling, and search-based testing to identify such vulnerabilities. Our experiment on 4 real-world control software and 8 vehicles including quadrotors, rover, and fixed-wing airplane has discovered 10 real vulnerabilities. Our technique does not have false positives as it only reports when an exploit can be generated.
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