@inproceedings{be4f456ae5b540bca1a5c879141555fd,
title = "Intelligent Walk Authentication: Implicit Authentication When You Walk with Smartphone",
abstract = "The popularity of smartphone makes mobile phone security even more important. We proposed Intelligent Walking Authentication (IWA), a lightweight, non-disturbing and automatically update smartphone authentication scheme. By collecting phone acceleration sensor data and calculate statistical features while walking, gait feature vector is generated in real time and compared with gait feature vector template to complete the authentication. The authentication has low computational complexity and not require large amounts of tagged data as previous work. A success rate of 93.63\% is achieved on a 30person walking data set. A 91.00\% authentication success rate is achieved on a data set of 11 people real-life simulated scenarios. The experimental results show that IWA can effectively resist the attack behavior in the authentication process and perform well in different locations while only increasing the power by 78.22mW.",
keywords = "Authentication, gait feature vector, security, smartphone",
author = "Huiyong Li and Jiannan Yu and Qian Cao",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 ; Conference date: 03-12-2018 Through 06-12-2018",
year = "2019",
month = jan,
day = "21",
doi = "10.1109/BIBM.2018.8621353",
language = "英语",
series = "Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1113--1116",
editor = "Harald Schmidt and David Griol and Haiying Wang and Jan Baumbach and Huiru Zheng and Zoraida Callejas and Xiaohua Hu and Julie Dickerson and Le Zhang",
booktitle = "Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018",
address = "美国",
}