CVShield: Guarding Sensor Data in Connected Vehicle with Trusted Execution Environment
CVShield: Guarding Sensor Data in Connected Vehicle with Trusted Execution Environment
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CVShield：通过可信执行环境保护联网车辆中的传感器数据
DOI：
10.1145/3375706.3380552
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Henry X. Liu
中科院分区：
文献类型：
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作者：
Shengtuo Hu;Qi Alfred Chen;Jiwon Joung;Can Carlak;Yiheng Feng;Z. Morley Mao;Henry X. Liu
新兴的互联车辆(CV)技术使车辆能够与交通基础设施和其他车辆无线交换安全和机动性信息(例如位置和速度)。现有的CV应用严重依赖传感器输入(例如GPS)。然而，之前的研究表明，攻击者可以通过危害车辆和广播伪造的传感器数据来造成严重拥堵或增加安全风险。因此，确保传感器数据的完整性是非常必要的。为了防止受攻击的车辆发送伪造的传感器数据，我们提出了一个系统CVShield，它利用了硬件辅助安全方面的最新进展(例如ARM TrustZone)。CVShield可以确保传感器数据从读取到在车辆端传输的完整性。通常，我们将与传感器数据读取、处理、封装和传输相关的所有代码从富执行环境(REE)重新定位到可信执行环境(TEE)。但是，手动提取代码段既费力又容易出错。此外，为了减少攻击面，我们还应该最小化TEE中可信计算库的大小。为了实现这些目标，我们建议利用程序切片来自动提取代码段，并消除大型代码库中不相关的代码。初步结果表明，CVShield能够支持GPS数据读取，并且我们的优化可以消除TrustZone上下文切换带来的时间开销。
The emerging Connected Vehicle (CV) technology enables vehicles to wirelessly exchange safety and mobility information (e.g., location and speed) with traffic infrastructure and other vehicles. Existing CV applications heavily rely on sensor inputs (e.g., GPS). However, previous work has shown that the attacker can cause severe congestion or increased safety risks by compromising vehicles and broadcasting falsified sensor data. Thus, it is highly desirable to ensure the integrity of sensor data. In this paper, to prevent compromised vehicles from sending falsified sensor data, we propose a system CVShield, which utilizes the recent advances in hardware-assisted security (e.g., ARM TrustZone). CVShield can ensure the integrity of the sensor data from their reading to their transmission at the vehicle side. In general, we relocate all codes that are related to sensor data reading, processing, encapsulation, and transmission from the rich execution environment (REE) into the trusted execution environment (TEE). However, manually extracting code sections is laborious and error-prone. Also, we should minimize the size of the trusted computing base (TCB) in TEE to reduce the attack surface. To achieve these goals, we propose to leverage program slicing to automatically extract code sections and eliminating irrelevant codes in large codebases. Our initial results demonstrate that CVShield can support GPS data reading, and our optimization can eliminate the time overhead introduced by context switches of TrustZone.