The Automatic Dependant Surveillance-Broadcast (ADS-B) message scheme was designed without any authentication or encryption of messages in place. It is therefore easily possible to attack it, e.g., by injecting spoofed messages or modifying the transmitted Global Navigation Satellite System (GNSS) coordinates. In order to verify the integrity of the received information, various methods have been suggested, such as multilateration, the use of Kalman filters, group certification, and many others. However, solutions based on modifications of the standard may be difficult and too slow to be implemented due to legal and regulatory issues. A vantage far less explored is the location verification using public sensor data. In this paper, we propose LoVe, a lightweight message verification approach that uses a geospatial indexing scheme to evaluate the trustworthiness of publicly deployed sensors and the ADS-B messages they receive. With LoVe, new messages can be evaluated with respect to the plausibility of their reported coordinates in a location privacy-preserving manner, while using a data-driven and lightweight approach. By testing our approach on two open datasets, we show that LoVe achieves very low false positive rates (between 0 and 0.00106) and very low false negative rates (between 0.00065 and 0.00334) while providing a real-time compatible approach that scales well even with a large sensor set. Compared to currently existing approaches, LoVe neither requires a large number of sensors, nor for messages to be recorded by as many sensors as possible simultaneously in order to verify location claims. Furthermore, it can be directly applied to currently deployed systems thus being backward compatible.

翻译：自动相关监视广播（ADS-B）报文方案在设计之初并未包含任何消息认证或加密机制，因此极易受到攻击，例如注入伪造消息或修改传输的全球导航卫星系统（GNSS）坐标。为验证接收信息的完整性，已有多种方法被提出，如多点定位、卡尔曼滤波器使用、群组认证等。然而，基于标准修改的解决方案可能因法律和监管问题而难以实施且进展缓慢。一个较少被探索的视角是利用公共传感器数据进行位置验证。本文提出LoVe，一种轻量级消息验证方法，它采用地理空间索引方案来评估公开部署传感器的可信度及其接收的ADS-B消息。借助LoVe，新消息可在保持位置隐私的同时，通过数据驱动的轻量级方法对其报告坐标的合理性进行评估。通过在两个开放数据集上测试，我们表明LoVe实现了极低的假阳性率（介于0至0.00106之间）和极低的假阴性率（介于0.00065至0.00334之间），同时提供了一种实时兼容且可随大规模传感器集合良好扩展的方法。与现有方法相比，LoVe既不需要大量传感器，也不要求消息被尽可能多的传感器同时记录以验证位置声明。此外，它可直接应用于当前已部署的系统，因此具有后向兼容性。