Proceedings of the 2016 4th International Conference on Mechanical Materials and Manufacturing Engineering

Network Security Risk Prediction Based on Time-Varying Markov Model

Authors
Chao Zhou, Yajuan Guo, Wei Huang, Jing Guo, Daohua Zhu
Corresponding Author
Chao Zhou
Available Online October 2016.
DOI
10.2991/mmme-16.2016.49How to use a DOI?
Keywords
Safety risk prediction; Time-Varying Markov Model (TVMM); Network attack
Abstract

With the application of network technology, the risk of network security is gradually increasing. In order to predict the likelihood of network risks in real-time, a Time-Varying Markov Model (TVMM) for real-time risk probability prediction was proposed. The real-time risk probability prediction method is able to predict the probability of network risk in future exactly with a real-time-updating-state probability transition matrix of TVMM. The model is used to calculate the risk probability of the network at different risk levels in network attack environment. The result shows that TVMM has higher real-time objectivity and accuracy than the tradi-tional Markov model.

Copyright
© 2016, 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 2016 4th International Conference on Mechanical Materials and Manufacturing Engineering
Series
Advances in Engineering Research
Publication Date
October 2016
ISBN
10.2991/mmme-16.2016.49
ISSN
2352-5401
DOI
10.2991/mmme-16.2016.49How to use a DOI?
Copyright
© 2016, 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  - Chao Zhou
AU  - Yajuan Guo
AU  - Wei Huang
AU  - Jing Guo
AU  - Daohua Zhu
PY  - 2016/10
DA  - 2016/10
TI  - Network Security Risk Prediction Based on Time-Varying Markov Model
BT  - Proceedings of the 2016 4th International Conference on Mechanical Materials and Manufacturing Engineering
PB  - Atlantis Press
SP  - 212
EP  - 215
SN  - 2352-5401
UR  - https://doi.org/10.2991/mmme-16.2016.49
DO  - 10.2991/mmme-16.2016.49
ID  - Zhou2016/10
ER  -