Network Security Risk Prediction Based on Time-Varying Markov Model

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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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  -