Survey Paper on Genetically Optimized Face Image CAPTCHA

The increasing use of smartphones, tablets, and other mobile devices poses a signi_cant challenge in providing effective online security. CAPTCHAs, tests for distinguishing human and computer users, have traditionally been popular; however, they face particular dif_culties 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, CAPTCHA demonstrates a very high human success rate while ensuring a 0 % attack rate using three well-known face detection algorithms.