A Novel Method of User Identity Recognition Based on Finger Trajectory

Abstract

User identity recognition is the key shield to protect users’ privacy data from disclosure and embezzlement. The user identity of mobile devices such as mobile phones mainly includes fingerprint recognition, nine-grid password, face recognition, digital password, etc. Due to the requirements of computing resources and convenience of mobile devices, these verification methods have their own shortcomings. In this paper, a user identity recognition technology based on finger trajectory is proposed. Based on the analysis of the users’ finger trajectory data, the feature of the user's finger movement trajectory is extracted to realize the identification of the user. Also, in this paper, we design and implement an android app, through which we collect the real finger trajectory data of 34 people and use K-means clustering combined with Bayesian classification to recognize and distinguish the user identity. The experimental results show that the finger trajectory has a good performance on identifying the users, which can be constructed as a new low-cost scheme for mobile device user identity recognition.