The Journal of Machine Learning Research
ARTiFACIAL: automated reverse turing test using FACIAL features
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Telling humans and computers apart automatically
Communications of the ACM - Information cities
IMAGINATION: a robust image-based CAPTCHA generation system
Proceedings of the 13th annual ACM international conference on Multimedia
Asirra: a CAPTCHA that exploits interest-aligned manual image categorization
Proceedings of the 14th ACM conference on Computer and communications security
Machine learning attacks against the Asirra CAPTCHA
Proceedings of the 15th ACM conference on Computer and communications security
Attacks and design of image recognition CAPTCHAs
Proceedings of the 17th ACM conference on Computer and communications security
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Although image-based CAPTCHAs have been introduced to overcome the security level limitation of the previous text-based CAPTCHAs, image-based CAPTCHAs still have problems such as user-unfriendliness in answer inference and wasted transmission cost. To cope with these issues, we propose a novel image-text fusion CAPTCHA model which uses a single image augmented with text hints that helps the users to guess the answers of the CAPTCHA problems more conveniently. According to the experiment results, the proposed CAPTCHA scheme has a higher correct answer rate than that of the previous scheme since the proposed scheme is able to help the users to infer the correct answer of the given CAPTCHA image more easily using the available text hints.