HOTCOLD Block: Fooling Thermal Infrared Detectors with a Novel Wearable Design
AbstractAdversarial attacks on thermal infrared imaging expose the risk of related applications. Estimating the security of these systems is essential for safely deploying them in the real world. In many cases, realizing the attacks in the physical space requires elaborate special perturbations. These solutions are often impractical and attention-grabbing. To address the need for a physically practical and stealthy adversarial attack, we introduce HotCold Block, a novel physical attack for infrared detectors that hide persons utilizing the wearable Warming Paste and Cooling Paste. By attaching these readily available temperature-controlled materials to the body, HotCold Block evades human eyes efficiently. Moreover, unlike existing methods that build adversarial patches with complex texture and structure features, HotCold Block utilizes an SSP-oriented adversarial optimization algorithm that enables attacks with pure color blocks and explores the influence of size, shape, and position on attack performance. Extensive experimental results in both digital and physical environments demonstrate the performance of our proposed HotCold Block. Code is available: https://github.com/weihui1308/HOTCOLDBlock.
How to Cite
Wei, H., Wang, Z., Jia, X., Zheng, Y., Tang, H., Satoh, S., & Wang, Z. (2023). HOTCOLD Block: Fooling Thermal Infrared Detectors with a Novel Wearable Design. Proceedings of the AAAI Conference on Artificial Intelligence, 37(12), 15233-15241. https://doi.org/10.1609/aaai.v37i12.26777
AAAI Special Track on Safe and Robust AI