Research on the Security of Visual Reasoning CAPTCHA
Research on the Security of Visual Reasoning CAPTCHA Yipeng Gao1, Haichang Gao1*, Sainan Luo1, Yang Zi1, Shudong Zhang1, Wenjie Mao1, Ping Wang1, Yulong Shen1 and Jeff Yan2 1School of Computer Science and Technology, Xidian University 2Department of Computer and Information Science, Linkoping¨ University Abstract Text-based CAPTCHAs have long been the most widely CAPTCHA is an effective mechanism for protecting comput- used scheme because of their simple structure and low cost. ers from malicious bots. With the development of deep learn- Such a CAPTCHA relies on a text recognition problem to ing techniques, current mainstream text-based CAPTCHAs distinguish humans from computers [51]. To resist the attack, have been proven to be insecure. Therefore, a major effort has text-based CAPTCHAs are often specifically designed with been directed toward developing image-based CAPTCHAs, anti-segmentation features and anti-recognition features [6]. and image-based visual reasoning is emerging as a new di- However, with advances in segmentation and character recog- rection of such development. Recently, Tencent deployed nition technologies, most text-based CAPTCHAs have been the Visual Turing Test (VTT) CAPTCHA. This appears to solved [15], [5], [45], [32], [55], [14], [56], [13], [4], [57], have been the first application of a visual reasoning scheme. [60], and designers need to find a new way to achieve se- Subsequently, other CAPTCHA service providers (Geetest, curity. Subsequently, image-based CAPTCHAs have been NetEase, Dingxiang, etc.) have proposed their own visual proposed. The image-based scheme is more diverse in con- reasoning schemes to defend against bots. It is, therefore, tent and background, and thus, it seems to be more secure than natural to ask a fundamental question: are visual reason- the text-based scheme.
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