Affiliation:
1. Ruhr-University Bochum, Bochum, Germany
2. Ruhr-University Bochum
Abstract
A so-called completely automated public Turing test to tell computers and humans apart (CAPTCHA) represents a challenge-response test that is widely used on the Internet to distinguish human users from fraudulent computer programs, often referred to as bots. To enable access for visually impaired users, most Web sites utilize audio CAPTCHAs in addition to a conventional image-based scheme. Recent research has shown that most currently available audio CAPTCHAs are insecure, as they can be broken by means of machine learning at relatively low costs. Moreover, most audio CAPTCHAs suffer from low human success rates that arise from severe signal distortions.
This article proposes two different audio CAPTCHA schemes that systematically exploit differences between humans and computers in terms of auditory perception and language understanding, yielding a better trade-off between usability and security as compared to currently available schemes. Furthermore, we provide an elaborate analysis of Google’s prominent reCAPTCHA that serves as a baseline setting when evaluating our proposed CAPTCHA designs.
Funder
German Research Foundation
Publisher
Association for Computing Machinery (ACM)
Subject
Safety, Risk, Reliability and Quality,General Computer Science
Cited by
2 articles.
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1. Automatic Generation and Evaluation of Usable and Secure Audio reCAPTCHA;The 21st International ACM SIGACCESS Conference on Computers and Accessibility;2019-10-24
2. Audio CAPTCHA Techniques: A Review;Proceedings of the Second International Conference on Computational Intelligence and Informatics;2018