ThermoCAPTCHA: Privacy-Preserving Human Verification with Farm-Resistant Traceable Tokens

• URL: http://arxiv.org/abs/2603.05915v1
• Date: Fri, 06 Mar 2026 05:07:53 GMT
• Title: ThermoCAPTCHA: Privacy-Preserving Human Verification with Farm-Resistant Traceable Tokens
• Abstract summary: We present ThermoCAPTCHA, a novel privacy-preserving human verification system.<n>A lightweight YOLOv4-tiny model identifies human heat signatures from a single thermal capture.<n>Our prototype achieves 96.70% detection accuracy with a 73.60 ms verification latency on a low-powered server.
• Score: 3.010893618491329
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: CAPTCHAs remain a critical defense against automated abuse, yet modern systems suffer from well-known limitations in usability, accessibility, and resistance to increasingly capable bots and low-cost CAPTCHA farms. Behavioral and puzzle-based mechanisms often impose cognitive burdens, collect extensive interaction data, or permit outsourcing to human solvers. In this paper, we present ThermoCAPTCHA, a novel privacy-preserving human verification system that uses real-time thermal imaging to detect live human presence without requiring users to solve challenges. A lightweight YOLOv4-tiny model identifies human heat signatures from a single thermal capture, while cryptographically bound traceable tokens prevent forwarding attacks by CAPTCHA farm workers. Our prototype achieves 96.70% detection accuracy with a 73.60 ms verification latency on a low-powered server. Comprehensive security evaluation, including MITM manipulation, spoofing attempts, adversarial perturbations, and misuse scenarios, shows that ThermoCAPTCHA withstands threats that commonly defeat behavioral CAPTCHAs. A user study with 50 participants, including visually challenged users, demonstrates improved accuracy, faster completion times, and higher perceived usability compared to reCAPTCHA v2.

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