Infrastructure-Enabled GPS Spoofing Detection and Correction
Infrastructure-Enabled GPS Spoofing Detection and Correction
复制标题
DOI：
10.1109/tits.2023.3298785
复制
发表时间：
2022-02
影响因子：
8.5
通讯作者：
Feilong Wang;Yuan Hong;X. Ban
中科院分区：
文献类型：
--
作者：
Feilong Wang;Yuan Hong;X. Ban
准确和稳健的定位对于支持高水平的驾驶自动化和安全至关重要。现代定位解决方案依赖于各种传感器，其中GPS已经并将继续是必不可少的。然而，GPS很容易受到恶意攻击，GPS欺骗已被确定为高度威胁。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，本研究探索了应用基础设施数据来防御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的、安全的数据源。构造了一个基于隔离森林的实时检测器来检测GPS欺骗。一旦检测到欺骗，就会隔离GPS测量，并使用安全的基础设施数据来修正可能受到危害的位置估计器。我们使用仿真和真实世界的数据对所提出的方法进行了测试，并证明了该方法在防御各种GPS欺骗攻击方面的有效性，其中包括针对产品级自动驾驶系统的隐身攻击。
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.