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Hiding from infrared detectors in real world with adversarial clothes

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Abstract

Thermal infrared detection is widely used in many scenarios including fast body temperature monitoring, safety monitoring and autopilot, however, its safety research has not attracted sufficient attention. We proposed the adversarial clothing to test the safety of infrared detection, which could hide from infrared detectors in the real world. The adversarial clothing uses flexible carbon fiber heaters as the basic elements. We optimized the patterns formed by different heaters based on the adversarial example technique. The optimized pattern lowered the average precision (AP) of YOLOv3 by 66.33%, while the random pattern lowered the AP by only 31.33% in the digital world. We then manufactured the adversarial clothing and tested the safety of infrared detectors in the physical world. The adversarial clothing lowered the AP of YOLOv3 by 43.95%, while the clothing with randomly placed heaters lowered the AP of YOLOv3 by only 19.21%. With ensemble attack techniques, our attack method had good transferability to unseen CNN models. We tested five typical defense methods but achieved limited success. These results indicate that current thermal infrared detectors are not robust.

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Data Availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Notes

  1. We have made the THU_TIR dataset public. https://github.com/zxp555/THU_TIR-dataset

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grants 61734004, U19B2034, 62061136001 and the Tsinghua-Toyota Joint Research Fund.

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Authors and Affiliations

  1. School of Integrated Circuits, Tsinghua University, Beijing, 100084, China

    Xiaopei Zhu & Zheyao Wang

  2. Department of Computer Science and Technology, Institute for Artificial Intelligence, State Key Laboratory of Intelligent Technology and Systems, THBI, BNRist, Tsinghua University, Beijing, 100084, China

    Zhanhao Hu, Siyuan Huang, Jianmin Li & Xiaolin Hu

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  1. Xiaopei Zhu
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Correspondence to Xiaolin Hu or Zheyao Wang.

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All experiments involving human participation were approved by the Department of Psychology Ethics Committee, Tsinghua University, Beijing, China.

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Zhu, X., Hu, Z., Huang, S. et al. Hiding from infrared detectors in real world with adversarial clothes. Appl Intell 53, 29537–29555 (2023). https://doi.org/10.1007/s10489-023-05102-5

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