The Failure of Noise-Based Non-continuous Audio Captchas

CAPTCHAs, which are automated tests intended to distinguish humans from programs, are used on many web sites to prevent bot-based account creation and spam. To avoid imposing undue user friction, CAPTCHAs must be easy for humans and difficult for machines. However, the scientific basis for successful CAPTCHA design is still emerging. This paper examines the widely used class of audio CAPTCHAs based on distorting non-continuous speech with certain classes of noise and demonstrates that virtually all current schemes, including ones from Microsoft, Yahoo, and eBay, are easily broken. More generally, we describe a set of fundamental techniques, packaged together in our Decaptcha system, that effectively defeat a wide class of audio CAPTCHAs based on non-continuous speech. Decaptcha's performance on actual observed and synthetic CAPTCHAs indicates that such speech CAPTCHAs are inherently weak and, because of the importance of audio for various classes of users, alternative audio CAPTCHAs must be developed.