Airport security scanners are vulnerable to waveform attacks that can hide weapons or project fake objects onto the operator's screen.
April 24, 2026
Original Paper
Adversarial Robustness of Near-Field Millimeter-Wave Imaging under Waveform-Domain Attacks
arXiv · 2604.21774
The Takeaway
Millimeter-wave scanners at airport security checkpoints can be fooled by specifically manipulated signal waveforms. These attacks conceal hidden targets or project fake objects into the scanner display without physically touching the machine. Traditional imaging algorithms are particularly susceptible to these interference patterns. Deep-learning models offer slightly better protection, but the fundamental physics of the signal still allows for significant blind spots. Security protocols may need an overhaul to account for simple signal-jamming devices that make weapons invisible to high-tech sensors.
From the abstract
Near-field millimeter-wave (mmWave) imaging is widely deployed in safety-critical applications such as airport passenger screening, yet its own security remains largely unexplored. This paper presents a systematic study of the adversarial robustness of mmWave imaging algorithms under waveform-domain physical attacks that directly manipulate the image reconstruction process. We propose a practical white-box adversarial model and develop a differential imaging attack framework that leverages the d