Thermally Activated Dual-Modal Adversarial Clothing against AI Surveillance Systems

• URL: http://arxiv.org/abs/2511.09829v2
• Date: Mon, 17 Nov 2025 14:14:26 GMT
• Title: Thermally Activated Dual-Modal Adversarial Clothing against AI Surveillance Systems
• Authors: Jiahuan Long, Tingsong Jiang, Hanqing Liu, Chao Ma, Wen Yao,
• Abstract summary: Adversarial patches have emerged as a popular privacy-preserving approach for resisting AI-driven surveillance systems.<n>We propose a thermally activated adversarial wearable designed to ensure adaptability and effectiveness in real-world environments.
• Score: 19.781690575288696
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Adversarial patches have emerged as a popular privacy-preserving approach for resisting AI-driven surveillance systems. However, their conspicuous appearance makes them difficult to deploy in real-world scenarios. In this paper, we propose a thermally activated adversarial wearable designed to ensure adaptability and effectiveness in complex real-world environments. The system integrates thermochromic dyes with flexible heating units to induce visually dynamic adversarial patterns on clothing surfaces. In its default state, the clothing appears as an ordinary black T-shirt. Upon heating via an embedded thermal unit, hidden adversarial patterns on the fabric are activated, allowing the wearer to effectively evade detection across both visible and infrared modalities. Physical experiments demonstrate that the adversarial wearable achieves rapid texture activation within 50 seconds and maintains an adversarial success rate above 80\% across diverse real-world surveillance environments. This work demonstrates a new pathway toward physically grounded, user-controllable anti-AI systems, highlighting the growing importance of proactive adversarial techniques for privacy protection in the age of ubiquitous AI surveillance.

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