Real-World Adversarial Attacks on RF-Based Drone Detectors

TL;DR

This paper introduces the first physical RF attack on drone detectors that use spectrogram images, demonstrating how optimized I/Q perturbations can reliably evade detection without hardware issues.

Contribution

It develops a novel class-specific universal complex baseband waveform attack for RF-based drone detectors, enabling over-the-air evasion in real-world scenarios.

Findings

Modest I/Q perturbations can evade drone detection

The attack is effective across four drone types

Perturbations do not interfere with legitimate signals

Abstract

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.