Game-based image semantic CAPTCHA on handset devices

Abstract

A completely automated public turing test to tell computer and human apart (CAPTCHA) is based on the Turing test, which aims to protect Internet services from automatic script attacks and spams. However, most proposed or deployed CAPTCHAs have been breached. It is possible to enhance the security of an existing CAPTCHA by adding noises systematically adding noises, but distortions would make characters recognition difficult for humans. On the other hand, most of the traditional CPATCHAs require complicated operations using keyboards and mice which may become limitations of modern handset devices. In this study, we propose a novel GISCHA using game-based image semantics with the contributions that 1) use simple keys, mouse, gesture, and accelerometer instead of complex alphabet inputs; 2) is language independent; 3) enhances the security level without annoying users; 4) is based on more advanced human cognitive abilities; and 5) make CAPTCHAs more interesting. The experiment results show that a single GISCHA challenge was completed in 9.06 s on average with a virtual keyboard and 10.25 s on average with accelerometers build in handset devices, and the pass rate of first time use is 94.8 %, which means that it is sufficiently easy for practical use.