Cargando…
A Hybrid Deep Learning System for Real-World Mobile User Authentication Using Motion Sensors
With the popularity of smartphones and the development of hardware, mobile devices are widely used by people. To ensure availability and security, how to protect private data in mobile devices without disturbing users has become a key issue. Mobile user authentication methods based on motion sensors...
Autores principales: | Zhu, Tiantian, Weng, Zhengqiu, Chen, Guolang, Fu, Lei |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7412513/ https://www.ncbi.nlm.nih.gov/pubmed/32664506 http://dx.doi.org/10.3390/s20143876 |
Ejemplares similares
-
Performance Analysis of Motion-Sensor Behavior for User Authentication on Smartphones
por: Shen, Chao, et al.
Publicado: (2016) -
Electrocardiogram (ECG)-Based User Authentication Using Deep Learning Algorithms
por: Agrawal, Vibhav, et al.
Publicado: (2023) -
Authentication of Smartphone Users Based on Activity Recognition and Mobile Sensing
por: Ehatisham-ul-Haq, Muhammad, et al.
Publicado: (2017) -
Advances in user authentication
por: Dasgupta, Dipankar, et al.
Publicado: (2017) -
RUASN: A Robust User Authentication Framework for Wireless Sensor Networks
por: Kumar, Pardeep, et al.
Publicado: (2011)