Proceedings of the International Academic Conference on Frontiers in Social Sciences and Management Innovation (IAFSM 2018)

Research on Risk Assessment of Information System Based on Fuzzy Neural Network

Authors
Guangliang Zhu, Yuanbao Wang
Corresponding Author
Guangliang Zhu
Available Online March 2019.
DOI
10.2991/iafsm-18.2019.8How to use a DOI?
Keywords
Fuzzy comprehensive evaluation; Neural network; Risk assessment
Abstract

In this paper, a risk assessment model based on fuzzy comprehensive evaluation and neural network is constructed, which is applied to information system risk assessment. Firstly, the risk of information system is established. Secondly, the fuzzy comprehensive evaluation and neural network algorithm are analyzed, and the risk assessment method based on fuzzy neural network is established. Finally, an example is given to verify the feasibility and scientific nature of the method.

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 International Academic Conference on Frontiers in Social Sciences and Management Innovation (IAFSM 2018)
Series
Advances in Economics, Business and Management Research
Publication Date
March 2019
ISBN
10.2991/iafsm-18.2019.8
ISSN
2352-5428
DOI
10.2991/iafsm-18.2019.8How 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  - Guangliang Zhu
AU  - Yuanbao Wang
PY  - 2019/03
DA  - 2019/03
TI  - Research on Risk Assessment of Information System Based on Fuzzy Neural Network
BT  - Proceedings of the International Academic Conference on Frontiers in Social Sciences and Management Innovation (IAFSM 2018)
PB  - Atlantis Press
SP  - 50
EP  - 55
SN  - 2352-5428
UR  - https://doi.org/10.2991/iafsm-18.2019.8
DO  - 10.2991/iafsm-18.2019.8
ID  - Zhu2019/03
ER  -