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fgCAPTCHA: Genetically Optimized Face Image CAPTCHA
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AI
DOI：10.1109/ACCESS.2014.2321001.png)
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Abstract
En 中文
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 40 000 CAPTCHA tests, fgCAPTCHA demonstrates a very high human success rate while ensuring a 0% attack rate using three well-known face detection algorithms.
Keywords:
Mobile security
web security
CAPTCHA
face detection
Journal
IF:
3.6
Papers:
9.8W
Citations:
29.4W
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