支持结构的GPS欺骗检测和纠正
Infrastructure-enabled GPS Spoofing Detection and Correction
摘要：
准确而强大的定位对于支持高水平的驾驶自动化和安全性至关重要。现代定位解决方案依赖于各种传感器，其中GPS一直是并将继续是必不可少的。然而，GPS可能容易受到恶意攻击，GPS欺骗已被确定为高威胁。随着交通基础设施在支持新兴车辆技术和系统方面变得越来越重要，本研究探讨了将基础设施数据应用于防御GPS欺骗的潜力。我们提出了一个支持基础设施的框架，使用路边单元作为独立、安全的数据源。基于隔离森林构造了一个实时检测器来检测GPS欺骗。一旦检测到欺骗，GPS测量就被隔离，并且使用安全的基础设施数据来校正潜在受损的位置估计器。我们使用模拟和真实数据测试了所提出的方法，并显示了其在防御各种GPS欺骗攻击方面的有效性，包括建议使生产级自动驾驶系统失败的隐形攻击。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
