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EmojiTCHA: Using Emotion Recognition to Tell Computers and Humans Apart

Abstract : Any successful CAPTCHA design must creatively balance the three competing criteria of usability, scalability, and robustness to achieve widespread deployment in public facing web services. We propose a novel CAPTCHA called EmojiTCHA which utilizes symbolic representations of human emotions in the form of emojis correlated to an image of real humans expressing the same emotion on their face. By leveraging the Project Oxford Emotion API from Microsoft’s cognitive services platform, which provides automated detection of human emotion expressions on human faces, we generate a tagged dataset in an automated fashion. Through the use of image warping and distortion techniques, we can significantly increase the robustness of the CAPTCHA against automated attacks, without compromising on usability, as confirmed by our user study.
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Submitted on : Monday, November 27, 2017 - 10:32:03 AM
Last modification on : Friday, August 9, 2019 - 3:24:28 PM


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David Lorenzi, Jaideep Vaidya, Achyuta Aich, Shamik Sural, Vijayalakshmi Atluri, et al.. EmojiTCHA: Using Emotion Recognition to Tell Computers and Humans Apart. 32th IFIP International Conference on ICT Systems Security and Privacy Protection (SEC), May 2017, Rome, Italy. pp.281-295, ⟨10.1007/978-3-319-58469-0_19⟩. ⟨hal-01649012⟩



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