SmileAuth: Using Dental Edge Biometrics for User Authentication on Smartphones
Hongbo Jiang, Hangcheng Cao, Daibo Liu, Jie Xiong, Zhichao Cao
Abstract
User authentication is crucial for security and privacy protection on smartphones. While a variety of authentication schemes are available on smartphones, security flaws have been continuously discovered. Fingerprint films can deceive fingerprint sensors and anti-surveillance prosthetic masks can spoof face recognition. In this paper, we propose a novel user authentication system SmileAuth that leverages the unique features of people's dental edge biometrics for reliable and convenient user authentication. SmileAuth extracts a series of dental edge features by slightly moving the smartphone to capture a few images from different camera angles. These unique features are determined by the tooth size, shape, position and surface abrasion. SmileAuth is robust against image spoofing, video-based attack, physically forced attack and denture attack. We implemented the prototype of SmileAuth on Android smartphones and comprehensively evaluated its performance by recruiting more than 300 volunteers. Experimental results show that SmileAuth can achieve an overall 99.74% precision, 98.69% F-score, 2.31% FNR and 0.25% FPR in diverse scenarios. Additional experiments with two pairs of twins demonstrate that dental edge biometrics are unique enough to effectively distinguish twins.
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