AdvDisplay: Adversarial Display Assembled by Thermoelectric Cooler for Fooling Thermal Infrared Detectors

Abstract

When the current physical adversarial patches cannot deceive thermal infrared detectors, the existing techniques implement adversarial attacks from scratch, such as digital patch generation, material production, and physical deployment. Besides, it is difficult to finely regulate infrared radiation. To address these issues, this paper designs an adversarial thermal display (AdvDisplay ) by assembling thermoelectric coolers (TECs) as an array. Specifically, to reduce the gap between patches in the physical and digital worlds and decrease the power of AdvDisplay device, heat transfer loss and electric power loss are designed to guide the patch optimization. In addition, a precise temperature control scheme for AdvDisplay is proposed based on proportional-integral-derivative (PID) control. Due to the accurate temperature regulation and the reusability of AdvDisplay , our method is able to improve the attack success rate and the efficiency of physical deployments. Extensive experimental results indicate that the proposed method possesses superior adversarial effectiveness compared to other methods and demonstrates strong robustness in physical attacks.

Cite

Text

Li et al. "AdvDisplay: Adversarial Display Assembled by Thermoelectric Cooler for Fooling Thermal Infrared Detectors." AAAI Conference on Artificial Intelligence, 2025. doi:10.1609/AAAI.V39I17.34011

Markdown

[Li et al. "AdvDisplay: Adversarial Display Assembled by Thermoelectric Cooler for Fooling Thermal Infrared Detectors." AAAI Conference on Artificial Intelligence, 2025.](https://mlanthology.org/aaai/2025/li2025aaai-advdisplay/) doi:10.1609/AAAI.V39I17.34011

BibTeX

@inproceedings{li2025aaai-advdisplay,
  title     = {{AdvDisplay: Adversarial Display Assembled by Thermoelectric Cooler for Fooling Thermal Infrared Detectors}},
  author    = {Li, Hao and Wan, Fanggao and Su, Yue and Wu, Yue and Zhang, Mingyang and Gong, Maoguo},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2025},
  pages     = {18279-18286},
  doi       = {10.1609/AAAI.V39I17.34011},
  url       = {https://mlanthology.org/aaai/2025/li2025aaai-advdisplay/}
}