无人机
计算机科学
乌克兰语
鉴定(生物学)
战场
航空学
计算机安全
工程类
语言学
遗传学
植物
生物
历史
哲学
古代史
作者
Conner Bender,Jason Staggs
标识
DOI:10.23919/cycon58705.2023.10181421
摘要
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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