Quality-based Score Level Fusion for Continuous Authentication with Motion Sensor and Face
Shixuan Wang, Jiabin Yuan, Shudi Chen · 2020
In the continuous authentication, single biometric has their own advantages, disadvantages and the most suitable application scenarios, which are often interfered with by various factors. When biometric information cannot be observed by the system, to solve the disadvantage that single biometric cannot continuously authenticate users, we integrate multiple biometrics to improve the security and reliability of the authentication system. In this paper, we describe the quality-based score level fusion for multimodal biometric continuous authentication. In this scheme, motion sensor and face are selected as biometric features. Meanwhile, one-class classifiers are used to train data, and sequential fusion is adopted. Combined with the quality scores of data, the probability densities of the samples are calculated by the Gaussian kernel density estimation. At the same time, the authentication scheme is implemented on mobile phones, and the authentication experiments are carried out on datasets and mobile phones.