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Filters: Author is Lin, Shen-Ho  [Clear All Filters]
2020-04-06
Shen, Sung-Shiou, Chang, Che-Tzu, Lin, Shen-Ho, Chien, Wei.  2019.  The Enhanced Graphic Pattern Authentication Scheme Via Handwriting identification. 2019 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE). :150–153.
Today, Smartphone is a necessary device for people connected to the Internet world. But user privacy and security are still playing important roles in the usage of mobile devices. The user was asked to enter related characters, numbers or drawing a simple graphic on the touch screen as passwords for unlocking the screensaver. Although it could provide the user with a simple and convenient security authentication mechanism, the process is hard to protect against the privacy information leakage under the strict security policy. Nowadays, various keypad lock screen Apps usually provides different type of schemes in unlocking the mobile device screen, such as simple-customized pattern, swipe-to-unlock with a static image and so on. But the vulnerability could provide a chance to hijacker to find out the leakage of graphic pattern information that influences in user information privacy and security.This paper proposes a new graphic pattern authentication mechanism to enhance the strength of that in the keypad lock screen Apps. It integrates random digital graphics and handwriting graphic input track recognition technologies to provide better and more diverse privacy protection and reduce the risk of vulnerability. The proposed mechanism is based on two factor identification scheme. First of all, it randomly changes digital graphic position based on unique passwords every time to increase the difficulty of the stealer's recording. Second, the input track of handwriting graphics is another identification factor for enhancing the complex strength of user authentication as well.