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adar Data Integrity Verification Using 2D QIM-Based Data Hiding
Sensors ( IF 3.9 ) Pub Date : 2020-09-27 , DOI: 10.3390/s20195530
Raghu Changalvala , Brandon Fedoruk , Hafiz Malik

The modern-day vehicle is evolved in a cyber-physical system with internal networks (controller area network (CAN), Ethernet, etc.) connecting hundreds of micro-controllers. From the traditional core vehicle functions, such as vehicle controls, infotainment, and power-train management, to the latest developments, such as advanced driver assistance systems (ADAS) and automated driving features, each one of them uses CAN as their communication network backbone. Automated driving and ADAS features rely on data transferred over the CAN network from multiple sensors mounted on the vehicle. Verifying the integrity of the sensor data is essential for the safety and security of occupants and the proper functionality of these applications. Though the CAN interface ensures reliable data transfer, it lacks basic security features, including message authentication, which makes it vulnerable to a wide array of attacks, including spoofing, replay, DoS, etc. Using traditional cryptography-based methods to verify the integrity of data transmitted over CAN interfaces is expected to increase the computational complexity, latency, and overall cost of the system. In this paper, we propose a light-weight alternative to verify the sensor data’s integrity for vehicle applications that use CAN networks for data transfers. To this end, a framework for 2-dimensional quantization index modulation (2D QIM)-based data hiding is proposed to achieve this goal. Using a typical radar sensor data transmission scenario in an autonomous vehicle application, we analyzed the performance of the proposed framework regarding detecting and localizing the sensor data tampering. The effects of embedding-induced distortion on the applications using the radar data were studied through a sensor fusion algorithm. It was observed that the proposed framework offers the much-needed data integrity verification without compromising on the quality of sensor fusion data and is implemented with low overall design complexity. This proposed framework can also be used on any physical network interface other than CAN, and it offers traceability to in-vehicle data beyond the scope of the in-vehicle applications.

中文翻译:

使用基于2D QIM的数据隐藏进行的adar数据完整性验证

现代汽车是在具有内部网络(控制器局域网(CAN),以太网等)连接数百个微控制器的电子物理系统中发展的。从传统的核心车辆功能(例如车辆控制,信息娱乐和动力总成管理)到最新的发展(例如高级驾驶员辅助系统(ADAS)和自动驾驶功能),每一项都使用CAN作为其通信网络主干。自动驾驶和ADAS功能依赖于通过CAN网络从车辆上安装的多个传感器传输的数据。验证传感器数据的完整性对于乘员的安全性和这些应用程序的正常功能至关重要。尽管CAN接口可确保可靠的数据传输,但它缺乏基本的安全功能,包括消息身份验证,这使其很容易遭受各种攻击,包括欺骗,重放,DoS等。使用传统的基于密码学的方法来验证通过CAN接口传输的数据的完整性预计会增加计算复杂性,延迟,和系统的整体成本。在本文中,我们提出了一种轻量级的替代方案,以验证使用CAN网络进行数据传输的车辆应用中传感器数据的完整性。为此,提出了一种基于二维量化索引调制(2D QIM)的数据隐藏框架以实现此目标。在自动驾驶汽车应用中使用典型的雷达传感器数据传输场景,我们分析了所提出的框架在检测和定位传感器数据篡改方面的性能。通过传感器融合算法研究了嵌入引起的失真对使用雷达数据的应用的影响。据观察,提出的框架提供了急需的数据完整性验证,而不会损害传感器融合数据的质量,并且以较低的总体设计复杂度实现。该提议的框架还可以在CAN以外的任何物理网络接口上使用,并且它提供了对车载数据的可追溯性,超出了车载应用程序的范围。
更新日期:2020-09-28
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