Scanning-to-speech challenge-response authentication test for visually impaired. (June 2021) - Chithra, P.L.; Sathya, K.
Highlights: Novel Scanning-to-Speech CAPTCHA is specially designed for the visually impaired. Users should not type it as they listen or read rather they should revamp it. End-to-end encryption is applied and random text is encrypted as QR code. It is implemented against the hidden Markov model and fuzzy solver. Not distorted, no noise in the form of arcs, no background confusion. Abstract: Completely Automated Public Turing Tests to Tell Computer and Humans Apart (CAPTCHA) is an approach used to distinguish between a self-active computer program and a human. This kind of CAPTCHA is used in the field of computing to discover a particular user interacting with the system is human or not. It requires someone to enter the correct sequence of digits, characters, or both the combinations. The average time taken to solve the current captcha displayed will take around 10 s approximately. Research findings also discover additionally that the numerous famous CAPTCHA procedures are not powerful or secure, further entangling the test of offering services acquired from robotic intervention yet available to individuals with disabilities. This leads to the formulation of new approaches like QR Code Scanning-to-Speech, Revamping, and Randomness. This technique is encrypted end-to-end by using Blowfish Fermat Little Theorem (BFLT). There are a total of 156 physical users (both visually impaired and visually fit) were analyzed to assess the potency of the proposed approach. Further, it is compared with the current highest development CAPTCHA to test the performance of the QR Code Scanning-to-Speech, Revamping, and Randomness. The security scrutiny proved that the proposed approach is robust and hindering Hidden Markov Model (HMM), Fuzzy solver, and recent eminent attacks. Graphical abstract: Image, graphical abstract