An audio CAPTCHA to distinguish humans from computers
This addresses security needs for online systems by providing an accessible CAPTCHA, but it is incremental as it builds on existing audio-based methods.
The paper tackles the problem of distinguishing humans from bots in security by proposing a new audio CAPTCHA that analyzes voice gaps rather than auditory perception, achieving a human success rate of about 97% and an attack pass rate of only 4% with an average solve time of 7.8 seconds.
CAPTCHAs are employed as a security measure to differentiate human users from bots. A new sound-based CAPTCHA is proposed in this paper, which exploits the gaps between human voice and synthetic voice rather than relays on the auditory perception of human. The user is required to read out a given sentence, which is selected randomly from a specified book. The generated audio file will be analyzed automatically to judge whether the user is a human or not. In this paper, the design of the new CAPTCHA, the analysis of the audio files, and the choice of the audio frame window function are described in detail. And also, some experiments are conducted to fix the critical threshold and the coefficients of three indicators to ensure the security. The proposed audio CAPTCHA is proved accessible to users. The user study has shown that the human success rate reaches approximately 97% and the pass rate of attack software using Microsoft SDK 5.1 is only 4%. The experiments also indicated that it could be solved by most human users in less than 14 seconds and the average time is only 7.8 seconds.