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HuMan: an accessible, polymorphic and personalized CAPTCHA interface with preemption feature tailored for persons with visual impairments

机译:人类:可访问的,多态和个性化CAPTCHA接口,用于视觉损伤的人量身定制的抢占功能

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摘要

Completely Automated Public Turing test to tell Computers and Humans Apart (CAPTCHA) is one of the major security components in the provision of fair web access by differentiating human access from malicious, automated access by bots. Though the CAPTCHA strengthens the security aspect of web access, their accessibility to people with visual impairments has inherent unresolved challenges. This paper presents an accessible CAPTCHA model termed HuMan (human or machine?) which aims at providing an audio-based CAPTCHA for people with visual impairments. The HuMan model incorporates personalization into the CAPTCHA access. The polymorphic nature of resolving the HuMan CAPTCHA facilitates kaleidoscopic behavior in CAPTCHA rendering. The presence of ambient noise and requirement of common sense knowledge to answer the questions presented by HuMan CAPTCHA model makes it friendlier toward human users. The HuMan model has a CAPTCHA preemption feature which enables the user to stop the challenge audio as soon as the answer is identified. The results of experiments conducted on the prototype implementation of HuMan model project the mean success rate of 92.46 % and system usability scale score of 82.44 for persons with visual impairments and 82.63 for sighted users.
机译:完全自动化的公共图灵测试,告诉计算机和人类分开(CAPTCHA)是通过区分人类从恶意,自动访问By Bots提供公平的网络访问中的主要安全组件之一。虽然CAPTCHA加强了网络访问的安全方面,但他们对具有视觉损伤的人的可访问性具有固有的尚未解决的挑战。本文介绍了一个可访问的CAPTCHA模型,被称为人类(人类或机器?),其目的是为具有视觉损伤的人提供基于音频的CAPTCHA。人体模型将个性化纳入CAPTCHA访问权限。解决人类CAPTCHA的多态性性质促进了CAPTCHA渲染中的万花筒行为。环境噪声的存在和常识知识的要求,以回答人为CAPTCHA模型提出的问题使其更友好地对人类用户。人类模型具有CAPTCHA抢占功能,使用户能够在识别答案后立即停止挑战音频。对人类模型的原型实施进行的实验结果,其平均成功率为92.46%,系统可用性比得分为82.44,对于视力障碍的人和视力用户有82.63。

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