traumatic brain injury, military, post-concussive disorder, gene-expression

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Publication Date



Statler College of Engineering and Mining Resources


Lane Department of Computer Science and Electrical Engineering


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.

Source Citation

B. M. Powell, G. Goswami, M. Vatsa, R. Singh and A. Noore, "fgCAPTCHA: Genetically Optimized Face Image CAPTCHA 5," in IEEE Access, vol. 2, pp. 473-484, 2014. doi: 10.1109/ACCESS.2014.2321001 keywords: {face recognition;mobile computing;security of data;online security;face detection algorithms;automated computer attacks;touch-based input methods;novel image-based CAPTCHA;modern mobile environment;genetically optimized face image CAPTCHA;fgCAPTCHA;CAPTCHAs;Face recognition;Security;Face detection;Mobile handsets;Noise measurement;Mobile communication;Mobile security;web security;CAPTCHA;face detection}, URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6807630&isnumber=6705689


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