An Improved Network Risk Evaluation Method Based on Markov Game

Abstract:

Network security risk assessment is an important means of acquiring and mastering the current and future state of network, which is of great significance to maintain the safe operation of the network. This paper presents an improved risk assessment method based on Markov game that has simply changed the past, in which the risk status of the network assets were classified into fixed categories. Depending on the game relationship between fixing vulnerabilities and threat attacking, this method has more detailed characterization of the network risk. Network attacks and vulnerabilities are sorted, which reduces the state space, making the scale of model input greatly reduced, improving the assessment of large-scale network efficiency. Simulation results demonstrate the feasibility and effectiveness of this method.

• Periodical: Applied Mechanics and Materials (Volumes 556-562)
• Pages: 5893-5897
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.556-562.5893
• Online since: May 2014
• Authors: Wen Fen Liu*, Shu Wei Zhang
• Keywords: Markov Game, Network Security, Network Vulnerabilities, Risk Assessment

References

[1] Grobauer B, Walloschek T, and Stocker E. Understanding Cloud Computing Vulnerabilities. IEEE Security& Privacy, 2011, 9(2): 50-57.

DOI: 10.1109/msp.2010.115

[2] Gehani A, Kedem G. Rheostat: Real time risk management / Proceedings of the 7th International Symposium on Recent Advances in Intrusion Detection. French Riviera, France, 2004: 296-314.

DOI: 10.1007/978-3-540-30143-1_16

[3] Årnes A, Valeur F, Vigna G, et al. Using hidden markov models to evaluate the risks of intrusions. Recent Advances in Intrusion Detection. Springer Berlin Heidelberg, 2006: 145-164.

DOI: 10.1007/11856214_8

[4] X. ZH Chen, Q. H Zheng, et al. Quantitative hierarchical threat evaluation model for network security. Journal of Software, 2006, 17(4): 885- 897.

[5] L Chen, Leneutre J. A game theoretical framework on intrusion detection in heterogeneous networks. Information Forensics and Security, IEEE Transactions on, 2009, 4(2): 165-178.

DOI: 10.1109/tifs.2009.2019154

[6] YZ Wang, Ch Lin et al. Analysis for network attack-defense based on stochastic game model [J]. Chinese Journal of Computers, 2010, 33(9).

DOI: 10.3724/sp.j.1016.2010.01748

[7] Y Zhang, X. B Tan, X. L Cui and H. S Xi. Network security situation awareness approach based on Markov game model. Journal of Software, 2011, 22 (3): 495-508.

DOI: 10.3724/sp.j.1001.2011.03751

[8] X. L C, X. B T, Y Z, et al. A markov game theory-based risk assessment model for network information system /Proceedings of the 2008 International Conference on Computer Science and Software Engineering-Volume 03. IEEE Computer Society, 2008: 1057-1061.

DOI: 10.1109/csse.2008.949