首次实现对射频无人机探测器的物理攻击，干扰检测同时不影响正常通信。
Real-World Adversarial Attacks on RF-Based Drone Detectors
- 设计通用复数基带扰动波形，可直接通过射频链路发送。
- 在4种无人机上实测，小幅结构化扰动即显著降低检测率。
- 适用于真实场景中的对抗攻击研究，适合安全与防御方向读者。
基于射频（RF）的系统通过分析无人机的射频信号模式生成谱图图像，并由目标检测模型进行识别。现有针对图像模型的射频攻击通过修改数字特征实现，但难以在真实环境中部署，因数字扰动转换为可发射波形时易引入同步误差和干扰，且受限于硬件条件。本文提出首个针对射频图像类无人机探测器的物理攻击，优化出一类特定类别、通用的复数基带（I/Q）扰动波形，可与合法通信信号一同传输。我们在四类不同无人机上使用射频记录和过空气（OTA）实验验证了该攻击。结果表明，微小且有结构的I/Q扰动能兼容标准射频链路，在可靠降低目标无人机检测率的同时，仍保持对合法无人机的正常检测能力。
原文摘要 · Abstract (English)
Radio frequency (RF) based systems are increasingly used to detect drones by analyzing their RF signal patterns, converting them into spectrogram images which are processed by object detection models. Existing RF attacks against image based models alter digital features, making over-the-air (OTA) implementation difficult due to the challenge of converting digital perturbations to transmittable waveforms that may introduce synchronization errors and interference, and encounter hardware limitations. We present the first physical attack on RF image based drone detectors, optimizing class-specific universal complex baseband (I/Q) perturbation waveforms that are transmitted alongside legitimate communications. We evaluated the attack using RF recordings and OTA experiments with four types of drones. Our results show that modest, structured I/Q perturbations are compatible with standard RF chains and reliably reduce target drone detection while preserving detection of legitimate drones.
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