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Proposing a Scheme for Human Interactive Proof Test sing Plasma Effect
Author(s) -
Ali Et al.
Publication year - 2019
Publication title -
mağallaẗ baġdād li-l-ʿulūm
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.167
H-Index - 6
eISSN - 2411-7986
pISSN - 2078-8665
DOI - 10.21123/bsj.16.2.0409
Subject(s) - scheme (mathematics) , exploit , computer science , turing test , mathematical proof , optical character recognition , usability , usable , perception , animation , human–computer interaction , character (mathematics) , artificial intelligence , computer vision , multimedia , image (mathematics) , computer graphics (images) , computer security , biology , mathematical analysis , geometry , mathematics , neuroscience
Human Interactive Proofs (HIPs) are automatic inverse Turing tests, which are intended to differentiate between people and malicious computer programs. The mission of making good HIP system is a challenging issue, since the resultant HIP must be secure against attacks and in the same time it must be practical for humans. Text-based HIPs is one of the most popular HIPs types. It exploits the capability of humans to recite text images more than Optical Character Recognition (OCR), but the current text-based HIPs are not well-matched with rapid development of computer vision techniques, since they are either vey simply passed or very hard to resolve, thus this motivate that continuous efforts are required to improve the development of HIPs base text. In this paper, a new proposed scheme is designed for animated text-based HIP; this scheme exploits the gap between the usual perception of human and the ability of computer to mimic this perception and to achieve more secured and more human usable HIP. This scheme could prevent attacks since it's hard for the machine to distinguish characters with animation environment displayed by digital video, but it's certainly still easy and practical to be used by humans because humans are attuned to perceiving motion easily. The proposed scheme has been tested by many Optical Character Recognition applications, and it overtakes all these tests successfully and it achieves a high usability rate of 95%.

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