文章基本信息

标题：Identity Authentication Based on Sensors of Smartphone and Neural Networks
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作者：Jingyong Zhu ; Hanbing Fan ; Yichen Huang 等
期刊名称：Journal of Computer and Communications
印刷版ISSN：2327-5219
电子版ISSN：2327-5227
出版年度：2022
卷号：10
期号：7
页码：90-102
DOI：10.4236/jcc.2022.107006
语种：English
出版社：Scientific Research Publishing
摘要：The smartphone has become an indispensable electric device for most people since it can assist us in finishing many tasks such as paying and reading. Therefore, the security of smartphones is the most crucial issue to illegal users who cannot access legal users’ privacy information. This paper studies identity authentication using user action. This scheme does not rely on the password or biometric identification. It checks user identity just by user action features. We utilize sensors installed in smartphones and collect their data when the user waves the phone. We collect these data, process them and feed them into neural networks to realize identity recognition. We invited 13 participants and collected about 350 samples for each person. The sampling frequency is set at 200 Hz, and DenseNet is chosen as the neural network to validate system performance. The result shows that the neural network can effectively recognize user identity and achieve an authentication accuracy of 96.69 percent.
关键词：Identity AuthenticationSmartphoneMotion SensorNeural Network