Depth Discontinuities by Pixel-to-Pixel Stereo
International Journal of Computer Vision
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Stereo Matching with Linear Superposition of Layers
IEEE Transactions on Pattern Analysis and Machine Intelligence
Asirra: a CAPTCHA that exploits interest-aligned manual image categorization
Proceedings of the 14th ACM conference on Computer and communications security
Usability of CAPTCHAs or usability issues in CAPTCHA design
Proceedings of the 4th symposium on Usable privacy and security
A low-cost attack on a Microsoft captcha
Proceedings of the 15th ACM conference on Computer and communications security
CAPTCHA Security: A Case Study
IEEE Security and Privacy
ACM SIGGRAPH Asia 2009 papers
CAPTCHA: using hard AI problems for security
EUROCRYPT'03 Proceedings of the 22nd international conference on Theory and applications of cryptographic techniques
Sketcha: a captcha based on line drawings of 3D models
Proceedings of the 19th international conference on World wide web
Recognizing objects in adversarial clutter: breaking a visual captcha
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Building segmentation based human-friendly human interaction proofs (HIPs)
HIP'05 Proceedings of the Second international conference on Human Interactive Proofs
A highly legible CAPTCHA that resists segmentation attacks
HIP'05 Proceedings of the Second international conference on Human Interactive Proofs
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With the growth of the Internet, its wide-ranging services are increasingly being threatened by adverse and malicious attacks. CAPTCHAs have emerged as a standard security countermeasure against Internet attacks such as distributed denial of service attacks and botnets. However, many CAPTCHA schemes themselves have been found to be susceptible to automated attacks. The task of designing a good CAPTCHA scheme is still an open and challenging question, as a good CAPTCHA must fulfil two fundamental requirements; namely, it must be secure against automated attacks whilst being human usable. This paper presents STE3D-CAP-e, a human usable text-based CAPTCHA that is robust against a variety of attacks. STE3D-CAP-e adopts a novel 3D CAPTCHA approach designed to capitalise on the inherent human ability to perceive depth from stereoscopic images. By presenting CAPTCHA challenges using stereoscopic images, humans can distinguish the main text from the background clutter in 3D. The various issues that were considered and addressed in the design of STE3D-CAP-e are described, along with a formal definition of its underlying AI problem family. This paper also presents analysis of STE3D-CAP-e in terms of its security and usability.