Abstract
Text-based CAPTCHA has been used over decades with increasing difficulty to remain effective with OCR technique advance. Image-based CAPTCHA is supposed to step in as a better alternative. However, recognition-based image CAPTCHA is not robust enough to resist against either computer pattern recognition algorithms or brute-force attacks with exhaustivity approach. We present a new CAPTCHA design called Relacha to distinguish humans from bots by an image content correlation test. The new construction scheme adopts random walk among images with correlated contents, and utilizes human reasoning ability on inferring the relevance of images. Relacha challenges are generated dynamically by using images from real-time online search engine. The usability and robustness of the proposed scheme has been evaluated by both numerical analysis and empirical evidence. The results show that humans can solve Relacha conveniently and effectively with a high pass rate, while bot programs may succeed with slim chance.
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Acknowledgments
This material is based upon work supported by the China NSF grant No. 61472189, the CERNET Innovation Project under contract No. NGII20160601, the State Key Laboratory of Air Traffic Management System and Technology No. SKLATM201703, and the Innovation Projects of Beijing Engineering Research Center of Next Generation Internet and Applications. Opinions and conclusions expressed in this material are those of the authors and do not necessarily reflect the views of the sponsors.
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Wei, S., Wu, Q., Ren, M. (2017). Relacha: Using Associative Meaning for Image Captcha Understandability. In: Wang, G., Atiquzzaman, M., Yan, Z., Choo, KK. (eds) Security, Privacy, and Anonymity in Computation, Communication, and Storage. SpaCCS 2017. Lecture Notes in Computer Science(), vol 10656. Springer, Cham. https://doi.org/10.1007/978-3-319-72389-1_29
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DOI: https://doi.org/10.1007/978-3-319-72389-1_29
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