平衡竞争环境:装备乌克兰自由战士低成本无人机探测能力

Conner Bender, Jason Staggs
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摘要

在乌克兰这场史无前例的冲突中,大量使用了不对称作战战术和技术,包括使用无人机。特别是,大疆创新(DJI)无人机在冲突中发挥了重要作用,通过在战场上提供侦察和爆炸弹药,为对手双方的战术军事行动提供支持。同样的无人机也被用来在乌克兰全境提供人道主义援助。然而,乌克兰公开指责大疆帮助俄罗斯瞄准乌克兰平民,允许俄罗斯军队获得和使用一种名为AeroScope的专有大疆无人机跟踪系统。该系统使俄罗斯军队能够定位和瞄准驾驶大疆无人机的乌克兰平民,这经常导致对无人机操作员的动能打击。现代大疆无人机信标遥测和远程识别信息,使AeroScope系统能够识别和跟踪30英里外的无人机和操作员。成本和获取的方便性是阻碍乌克兰使用自己的AeroScope系统来识别和定位俄罗斯使用的大疆无人机和操作员的能力的主要因素。这为俄罗斯在战场上提供了不对称优势。尽管网络安全研究人员已经证明大疆无人机识别无线数据链是未加密的,但如何使用低成本和广泛可用的软件定义无线电实时收集和解码这些信号仍然是一个谜。本文通过反向工程大疆无人机识别信号和消息结构来检测OcuSync和增强型Wi-Fi数据链路上的无人机id,从而解决了这个问题。详细介绍了一个功能齐全的开源原型,可以使用两个HackRF One软件定义无线电检测大疆OcuSync无人机。该方法可以很容易地被其他人采用,以快速组装和部署低成本的大疆无人机和操作人员检测和地理定位系统,其功能类似于AeroScope系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Leveling the Playing Field: Equipping Ukrainian Freedom Fighters with Low-Cost Drone Detection Capabilities
The unprecedented conflict in Ukraine has seen heavy use of asymmetric warfare tactics and techniques, including the use of drones. In particular, Da-Jiang Innovations (DJI) drones have played a major role in the conflict, supporting tactical military operations for both opponents by providing reconnaissance and explosive ordnance across the battlefield. The same drones have also been leveraged to provide humanitarian aid across Ukraine. However, Ukraine has publicly accused DJI of helping Russia target Ukrainian civilians by allowing Russian military forces to acquire and use a proprietary DJI drone-tracking system called AeroScope. This system has allowed Russian forces to geolocate and target Ukrainian civilians piloting DJI drones, which has often led to kinetic strikes against drone operators. Modern DJI drones beacon telemetry and remote identification information that allows the AeroScope system to identify and track the drone and operator at ranges of up to 30 miles away. Cost and ease of access are the primary factors that have hindered Ukraine’s ability to counter this threat with AeroScope systems of their own to identify and locate DJI drones and operators used by Russia. This has provided an asymmetric advantage to Russia on the battlefield. Although cybersecurity researchers have demonstrated that DJI drone identification wireless datalinks are unencrypted, it remains a mystery how to collect and decode these signals over the air in real time using low-cost and widely available software-defined radios. This paper addresses the problem by reverse engineering DJI drone identification signals and message structures to detect drone IDs over OcuSync and Enhanced Wi-Fi datalinks. A functioning open-source prototype is detailed that can detect DJI OcuSync drones using two HackRF One software-defined radios. The methodology can easily be adopted by others to rapidly assemble and deploy low-cost DJI drone and operator detection and geolocation systems that are functionally similar to the AeroScope system.
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