Network Security Risk Prediction Based on Time-Varying Markov Model
- https://doi.org/10.2991/mmme-16.2016.49How to use a DOI?
- Safety risk prediction; Time-Varying Markov Model (TVMM); Network attack
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.
- © 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 - https://doi.org/10.2991/mmme-16.2016.49 ID - Zhou2016/10 ER -