Proceedings of the 2019 International Conference on Big Data, Electronics and Communication Engineering (BDECE 2019)

Opportunities and Challenges for Social Security Work in a Big Data Environment

Authors
Yu Zhou, Bei Ye
Corresponding Author
Yu Zhou
Available Online 24 December 2019.
DOI
10.2991/acsr.k.191223.004How to use a DOI?
Keywords
big data, social security, opportunity challenge
Abstract

With the rapid development of the era of big data, the information road of social security has been accelerating. In China, social security is a vast livelihood problem and a huge and complex system. The powerful analytical and data processing capabilities of large data are just conducive to solving the problem of social security work with huge data. This paper mainly uses the literature research method to focus on the opportunities and challenges brought by big data to social security, and explore the development direction of social security in China under the big data environment.

Copyright
© 2019, 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/).

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Volume Title
Proceedings of the 2019 International Conference on Big Data, Electronics and Communication Engineering (BDECE 2019)
Series
Advances in Computer Science Research
Publication Date
24 December 2019
ISBN
10.2991/acsr.k.191223.004
ISSN
2352-538X
DOI
10.2991/acsr.k.191223.004How to use a DOI?
Copyright
© 2019, 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  - Yu Zhou
AU  - Bei Ye
PY  - 2019
DA  - 2019/12/24
TI  - Opportunities and Challenges for Social Security Work in a Big Data Environment
BT  - Proceedings of the 2019 International Conference on Big Data, Electronics and Communication Engineering (BDECE 2019)
PB  - Atlantis Press
SP  - 18
EP  - 20
SN  - 2352-538X
UR  - https://doi.org/10.2991/acsr.k.191223.004
DO  - 10.2991/acsr.k.191223.004
ID  - Zhou2019
ER  -