论文标题
支持基础设施的GPS欺骗检测和校正
Infrastructure-enabled GPS Spoofing Detection and Correction
论文作者
论文摘要
准确，稳健的本地化对于支持高级驾驶自动化和安全至关重要。现代本地化解决方案依赖于各种传感器，其中GP一直并将继续至关重要。但是，全科医生可能容易受到恶意攻击，而GPS欺骗已被确定为高威胁。随着运输基础设施在支持新兴的车辆技术和系统方面越来越重要，本研究探讨了应用基础设施数据以防御GPS欺骗的潜力。我们建议使用路边单元作为独立的，有担保的数据源提出一个支持基础设施的框架。基于隔离林的实时检测器的构建是为了检测GPS欺骗。一旦检测到欺骗，GPS测量将隔离，并使用安全的基础架构数据校正了潜在损害的位置估计器。我们使用仿真和现实世界数据测试了提出的方法，并显示了其在防御各种GPS欺骗攻击方面的有效性，包括拟议失败生产级自动驾驶系统的隐秘攻击。
Accurate and robust localization is crucial for supporting high-level driving automation and safety. Modern localization solutions rely on various sensors, among which GPS has been and will continue to be essential. However, GPS can be vulnerable to malicious attacks and GPS spoofing has been identified as a high threat. With transportation infrastructure becoming increasingly important in supporting emerging vehicle technologies and systems, this study explores the potential of applying infrastructure data for defending against GPS spoofing. We propose an infrastructure-enabled framework using roadside units as an independent, secured data source. A real-time detector, based on the Isolation Forest, is constructed to detect GPS spoofing. Once spoofing is detected, GPS measurements are isolated, and the potentially compromised location estimator is corrected using secure infrastructure data. We test the proposed method using both simulation and real-world data and show its effectiveness in defending against various GPS spoofing attacks, including stealthy attacks that are proposed to fail the production-grade autonomous driving systems.
