A Novel Network Survivability Analysis and Evaluation Model

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Network survivability has the characteristics of complexity, dynamic evolution and uncertainty, which has become one of the most important factors for analyzing and evaluating network performance. Network survivability analysis and evaluation is a process of analyzing and quantifying the degree to which network system can survive in network threats. This paper proposes a novel network survivability analysis and evaluation model.Firstly, network survivability is abstracted as a dynamic game process among network attacker, network defender and normal user, thereafter network survivability evolutionary game model is established and network survivability analysis algorithm is proposed based on the game model. Secondly, the survivability characteristics of the network can be measured and evaluated based on the analyzed information based on the proposed immune evolutionary algorithm for network survivability metric weight solving and network survivability evaluation method using multiple criteria decision making. Finally, the proposed network survivability analysis and evaluation model is experimented in a typical network environment and the correctness and effectiveness of the model is validated through experimental analysis.

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2082-2088

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August 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] John C. Knight, Kevin J. Sullivan. On the Definition of Survivability. University of Virginia, Department of Computer Science, Technical Report CS-TR-33-00.

Google Scholar

[2] Fisher J, Linger R. Survivability: protecting your critical systems[J]. IEEE Journal of Internet Compu¬ting, 1999, 3(6): 55~63.

DOI: 10.1109/4236.807008

Google Scholar

[3] Louca Soulla, Pitsillides Andreas, Samaras George. On Network Survivability Algorithms Based on Trellis Graph Transformations[C]. The Fourth IEEE Symposium on Computers and Communica¬tions(ISCC'99), Red Sea, Egypt, 1999: 235-243.

DOI: 10.1109/iscc.1999.780817

Google Scholar

[4] Krings Axel W, Azadmanesh M H. A Graph Based Model for Survivability Analysis[R]. Technical Report UI-CS-TR-02-024, Computer Science Department, University of Idaho, (2002).

Google Scholar

[5] Zolfaghari Ali, Kaudel Fred J. Framework for Network Survivability Performance[J]. IEEE Journal on¬Seleeted Areas in Communications, 1994, 12(1): 46-51.

DOI: 10.1109/49.265703

Google Scholar

[6] MeDemrott J. Attaek-Potential-Based Survivability Modeling for High-Consequence Systems[C]. Third IEEE International Workshop on Information Assurance(IWIA'05), College Park, Maryland, US, 2005: 119-130.

DOI: 10.1109/iwia.2005.4

Google Scholar

[7] Dong Seong Kim, Khaja Mohammad Shazzad, Jong Sou Park. A Framework of Survivability Model for Wireless Sensor Network[C]. Proeeedings of the First International Conference on Availability, Reliability and Security, Washington DC, US, 2006: 512-522.

DOI: 10.1109/ares.2006.6

Google Scholar

[8] Jha Sanjay K, Wing Jeannette M, Linger Richard C, et al. Survivability Analysis of Network Specifica¬tions[C]. International Conference on Dependable Systems and Networks(DSN2000), New York, USA, 2000: 613-622.

DOI: 10.1109/icdsn.2000.857597

Google Scholar

[9] Gao Zhixing, Ong Chen Hui, Tan Woon Kiong. Survivability Assessment: Modeling Dependencies in Information Systems[C]. The 4th IEEE/CMU/SEI Information Survivability Workshop(ISW-2001/2002), Va¬neouver, BC Canada, 2001: 515-522.

Google Scholar

[10] Hevner Alan, Linger Riehard. The Flow-Service-Quality Framework: Unified Engineering for Large-scale, Adaptive Systems[C]. The 35th Hawaii International Conference on System Sciences, Hawaii, US, 2002: 4006-4015.

DOI: 10.1109/hicss.2002.994480

Google Scholar

[11] R. Ellison, D. Fisher, R. Linger, H. Lipson, T. Longstaff, and N. Mead. Survivable network systems: An emerging discipline. Technical Report CMU/SEI-97-153, Software Engineering Institute, Carnegie Mellon University, Pittsburgh, PA15213, November (1997).

DOI: 10.21236/ada341963

Google Scholar

[12] Lin Xue-gang, Zhu shen-liang, Xu Rong-sheng. Layered computation for information system survivability. Journal of Zhejiang University (Engineering Science), 2006, 40(11): 1960-(1965).

Google Scholar

[13] Sallhammar K, Knapskog S J, Helvik B E. Using stochastic game theory to compute the expected behavior of attackers. In: Proc. Of the 2005 Symp. on Applications and the Internet Workshops. (2005).

DOI: 10.1109/saintw.2005.1619988

Google Scholar

[14] Shen D, Chen G, Cruz J B, Haynes J L, Kruger M, Blasch E. A Markov game theoretic approach for cyber situational awareness. In: Dasarathy BV, ed. Proc. of the Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications, Vol. 6571, 65710F. (2007).

DOI: 10.1117/12.720090

Google Scholar

[15] Ding Yong-sheng. A new scheme for computational intelligence: bio-network architecture, CAAI Transactions on Intelligent Systems. 2007, 2(2): 26-30.

Google Scholar

[16] Ding Yong-sheng. Design of a bio-network architecture based on immune emergent computation. Control and Decision, 2003, 18(2): 155-159.

Google Scholar