发表机构
Duke University（杜克大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对现有无人机重定向攻击可靠性、精准度不足的问题，提出幻影导航器攻击方法，结合离线可达性分析与在线闭环执行层，构建含激光雷达-相机栈的物理平台，实现隐蔽精准的无人机重定向，经案例验证有效。
AI 中文摘要
将无人机（UAV）从其预定任务轨迹重定向是一个活跃的研究领域。然而，现有的无人机重定向攻击在针对性转移方面缺乏可靠性、精准度和隐蔽性，它们主要依赖物理捕获、通信劫持或传感器欺骗。但物理拦截成本高昂，仅提供一次成功机会，且附带损伤风险高；基于网络的攻击需要深厚的技术专业知识以及对加密通信通道的访问权限；而传感器欺骗技术通常无法达到将无人机引导至指定目标所需的精度和鲁棒性。因此，我们提出了幻影导航器（Phantom Navigator），这是一种可隐蔽且精准地误导无人机前往指定欺骗目标的无人机重定向攻击方法。我们的方法结合了离线重定向前可达性分析（该分析提供可实现重定向范围的高保真估计）与在线闭环隐蔽执行层，以确保实践中的重定向成功。基于此方法，我们构建了一个物理攻击平台，配备了激光雷达（LiDAR）-相机检测、跟踪与欺骗栈，该栈可执行实时识别、位姿估计以及目标欺骗信号的计算，从而隐蔽且精准地将受攻击的无人机重定向至指定位置。我们在真实世界案例研究中验证了该重定向方法及攻击实现的有效性。
英文摘要
Redirecting unmanned aerial vehicles (UAVs) from their intended mission trajectories has been an active area of research. However, existing UAV redirection attacks lack reliability, precision, and covertness for a targeted diversion. They primarily rely on physical capture, communication hijacking, or sensor spoofing. Yet, physical interception is costly, offers only a single opportunity for success, and poses a high risk of collateral damage; network-based attacks demand deep technical expertise and access to encrypted communication channels; and sensor spoofing techniques typically fall short in achieving the accuracy and robustness required to steer a UAV toward a specified target. Consequently, we propose Phantom Navigator, a UAV redirection attack to mislead drones to a designated spoofing target, covertly and precisely. Our approach combines offline pre-redirection reachability analysis, which provides high-fidelity estimates of achievable redirect ranges, with an online closed-loop, stealthy execution layer that ensures successful redirection in practice. Based on this approach, we build a physical attack platform equipped with a LiDAR--camera detection, tracking, and spoofing stack that performs real-time identification, pose estimation, and computation of targeted spoofing signals to covertly and accurately redirect victim UAVs to a designated location. We demonstrate the effectiveness of our redirection methodology and the attack implementation in real-world case studies.
