HOTCOLD Block: Fooling Thermal Infrared Detectors with a Novel Wearable Design

Authors

  • Hui Wei National Engineering Research Center for Multimedia Software, Institute of Artificial Intelligence, School of Computer Science, Wuhan University Hubei Key Laboratory of Multimedia and Network Communication Engineering
  • Zhixiang Wang The University of Tokyo RIISE National Institute of Informatics
  • Xuemei Jia National Engineering Research Center for Multimedia Software, Institute of Artificial Intelligence, School of Computer Science, Wuhan University Hubei Key Laboratory of Multimedia and Network Communication Engineering
  • Yinqiang Zheng The University of Tokyo
  • Hao Tang CVL, ETH Zurich
  • Shin'ichi Satoh National Institute of Informatics The University of Tokyo
  • Zheng Wang National Engineering Research Center for Multimedia Software, Institute of Artificial Intelligence, School of Computer Science, Wuhan University Hubei Key Laboratory of Multimedia and Network Communication Engineering

DOI:

https://doi.org/10.1609/aaai.v37i12.26777

Keywords:

General

Abstract

Adversarial 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.

Downloads

Published

2023-06-26

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

Issue

Section

AAAI Special Track on Safe and Robust AI