Algwil, Abdalnaser and Ciresan, Dan and Liu, Beibei and Yan, Jeff (2016) A security analysis of automated Chinese turing tests. In: ACSAC '16 Proceedings of the 32nd Annual Conference on Computer Security Applications : ACSAC 32. ACM, New York, pp. 520-532. ISBN 9781450347716
A_Security_Analysis_of_Automated_Chinese_Turing_Tests.pdf - Accepted Version
Available under License Creative Commons Attribution-NonCommercial.
Download (1MB)
Abstract
Text-based Captchas have been widely used to deter misuse of services on the Internet. However, many designs have been broken. It is intellectually interesting and practically relevant to look for alternative designs, which are currently a topic of active research. We motivate the study of Chinese Captchas as an interesting alternative design - counterintuitively, it is possible to design Chinese Captchas that are universally usable, even to those who have never studied Chinese language. More importantly, we ask a fundamental question: is the segmentation-resistance principle established for Roman-character based Captchas applicable to Chinese based designs? With deep learning techniques, we offer the first evidence that computers do recognize individual Chinese characters well, regardless of distortion levels. This suggests that many real-world Chinese schemes are insecure, in contrast to common beliefs. Our result offers an essential guideline to the design of secure Chinese Captchas, and it is also applicable to Captchas using other large-alphabet languages such as Japanese.