Typer vs. CAPTCHA: Private information based CAPTCHA to defend against crowdsourcing human cheating
Jianyi Zhang, Xiali Hei, Zhiqiang Wang

TL;DR
This paper introduces a novel CAPTCHA design that leverages private information and information asymmetry to effectively distinguish humans from Typer attacks, enhancing security without altering existing authentication protocols.
Contribution
The paper proposes a new CAPTCHA principle based on private information, formalizes two implementation examples, and demonstrates its effectiveness through user studies.
Findings
Humans can solve the CAPTCHA accurately within 20 seconds.
Typer attacks have a very low success rate against the proposed CAPTCHA.
The method does not require modifications to existing authentication systems.
Abstract
Crowdsourcing human-solving or online typing attacks are destructive problems. However, studies into these topics have been limited. In this paper, we focus on this kind of attacks whereby all the CAPTCHAs can be simply broken because of its design purpose. After pursuing a comprehensive analysis of the Typer phenomenon and the attacking mechanism of CAPTCHA, we present a new CAPTCHA design principle to distinguish human (Typer) from human (user). The core idea is that the challenge process of the CAPTCHA should contain the unique information with a private attribute. The notion of our idea is based on the information asymmetry between humans. Without this private information, Typers will not be able to finish the attack even if they recognize all the characters from the CAPTCHA. We formalize, design and implement two examples on our proposed principle, a character-based, and a…
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Taxonomy
TopicsUser Authentication and Security Systems · Spam and Phishing Detection · Privacy, Security, and Data Protection
