Proceedings of the International Conference on Computer Networks and Communication Technology (CNCT 2016)

Research on the Cyberspace Security Evaluation Model of Smart City based on the Big Data Analysis Technology

Authors
Yuan TAO, Yu-xiang ZHANG, Ming LI, Wen-rui MA
Corresponding Author
Yuan TAO
Available Online December 2016.
DOI
10.2991/cnct-16.2017.107How to use a DOI?
Keywords
Big data analysis, Cyberspace security of smart city, Evaluation model
Abstract

In order to evaluate the cyberspace security of smart city, a new cyberspace security evaluation model of smart city is proposed, which is based on the big data and the classified protection technology. The key performance indicator and analysis algorithm is provided to quantify the cyberspace security of smart city, so that the effective information can be extracted from the large amount of security data, and the cyberspace security situation of smart city can be analysis and evaluated.

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/).

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Volume Title
Proceedings of the International Conference on Computer Networks and Communication Technology (CNCT 2016)
Series
Advances in Computer Science Research
Publication Date
December 2016
ISBN
10.2991/cnct-16.2017.107
ISSN
2352-538X
DOI
10.2991/cnct-16.2017.107How 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  - Yuan TAO
AU  - Yu-xiang ZHANG
AU  - Ming LI
AU  - Wen-rui MA
PY  - 2016/12
DA  - 2016/12
TI  - Research on the Cyberspace Security Evaluation Model of Smart City based on the Big Data Analysis Technology
BT  - Proceedings of the International Conference on Computer Networks and Communication Technology (CNCT 2016)
PB  - Atlantis Press
SP  - 774
EP  - 778
SN  - 2352-538X
UR  - https://doi.org/10.2991/cnct-16.2017.107
DO  - 10.2991/cnct-16.2017.107
ID  - TAO2016/12
ER  -