@inproceedings{97d1552c60794cc796e8f8fe95452e03,
title = "POSTER: I Can't hear this because I am human: A novel design of audio CAPTCHA system",
abstract = "A CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) provides the first line of defense to protect websites against bots and automatic crawling. Recently, audio-based CAPTCHA systems are started to use for visually impaired people in many internet services. However, with the recent improvement of speech recognition and machine learning system, audio CAPTCHAs have come to struggle to distinguish machines from users, and this situation will likely continue to worsen. Unlike conventional CAPTCHA systems, we propose a new conceptual audio CAPTCHA system, combining certain sound, which is only understandable by a machine. Our experiment results demonstrate that the tested speech recognition systems always provide correct responses for our CAPTCHA samples while humans cannot possibly understand them. Based on this computational gap between the human and machine, we can detect bots with their correct responses, rather than their incorrect ones.",
keywords = "Bot, CAPTCHA, Machine learning, Speech recognition",
author = "Jusop Choi and Taekkyung Oh and William Aiken and Woo, \{Simon S.\} and Hyoungshick Kim",
note = "Publisher Copyright: {\textcopyright} 2018 Association for Computing Machinery.; 13th ACM Symposium on Information, Computer and Communications Security, ASIACCS 2018 ; Conference date: 04-06-2018 Through 08-06-2018",
year = "2018",
month = may,
day = "29",
doi = "10.1145/3196494.3201590",
language = "English",
series = "ASIACCS 2018 - Proceedings of the 2018 ACM Asia Conference on Computer and Communications Security",
publisher = "Association for Computing Machinery, Inc",
pages = "833--835",
booktitle = "ASIACCS 2018 - Proceedings of the 2018 ACM Asia Conference on Computer and Communications Security",
}