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FgCAPTCHA: Genetically Optimized Face Image CAPTCHA 5
B.M. Powell, G. Goswami, , , A. Noore
Published in Institute of Electrical and Electronics Engineers Inc.
Volume: 2
Pages: 473 - 484
The increasing use of smartphones, tablets, and other mobile devices poses a significant challenge in providing effective online security. CAPTCHAs, tests for distinguishing human and computer users, have traditionally been popular; however, they face particular difficulties in a modern mobile environment because most of them rely on keyboard input and have language dependencies. This paper proposes a novel image-based CAPTCHA that combines the touch-based input methods favored by mobile devices with genetically optimized face detection tests to provide a solution that is simple for humans to solve, ready for worldwide use, and provides a high level of security by being resilient to automated computer attacks. In extensive testing involving over 2600 users and 40000 CAPTCHA tests, fgCAPTCHA demonstrates a very high human success rate while ensuring a 0% attack rate using three well-known face detection algorithms. © 2013 IEEE.
About the journal
JournalData powered by TypesetIEEE Access
PublisherData powered by TypesetInstitute of Electrical and Electronics Engineers Inc.
Open AccessNo