Proceedings of the 3rd Workshop on Advanced Research and Technology in Industry (WARTIA 2017)

Research on Mobile Terminal User Identification Based on Big Data

Authors
Zhenhua Wang, Yangsen Yu, Tao Xue
Corresponding Author
Zhenhua Wang
Available Online November 2017.
DOI
10.2991/wartia-17.2017.42How to use a DOI?
Keywords
Mobile terminal, User identification, Big data analysis.
Abstract

Mobile user identity is an important part of mobile Internet security research. In this paper, it introduces the development status of user identification and authentication technology in "Internet +" era, and briefly describes their implementation plan and evolution trend. the security problem of each general authentication technology is analyzed. This paper describes the combination of mobile device identification, user behavior analysis and forecasting based on big data, and routine identification, and realizes mobile user identification to improve the accuracy of mobile user identification.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

Volume Title
Proceedings of the 3rd Workshop on Advanced Research and Technology in Industry (WARTIA 2017)
Series
Advances in Engineering Research
Publication Date
November 2017
ISBN
978-94-6252-409-5
ISSN
2352-5401
DOI
10.2991/wartia-17.2017.42How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Zhenhua Wang
AU  - Yangsen Yu
AU  - Tao Xue
PY  - 2017/11
DA  - 2017/11
TI  - Research on Mobile Terminal User Identification Based on Big Data
BT  - Proceedings of the 3rd Workshop on Advanced Research and Technology in Industry (WARTIA 2017)
PB  - Atlantis Press
SP  - 210
EP  - 213
SN  - 2352-5401
UR  - https://doi.org/10.2991/wartia-17.2017.42
DO  - 10.2991/wartia-17.2017.42
ID  - Wang2017/11
ER  -