Abstract
In order to enhance service survivability, an immune-based model for service survivability, referred to as ISSM, is presented. In the model, the concepts and formal definitions of self, nonself, immunocyte, diversity system, and etc., are given; the antibody concentration and the dynamic change process of host status are described. Building on the relationship between the antibody concentration and the state of an illness in the human immune system, the systemic service capability and the service risk are calculated quantitatively. Based on the differences of the immune system among individuals, a service survivability algorithm, dynamic service migration algorithm, is put forth. Simulation results show that the model is real-time and adaptive, thus providing an effective solution for service survivability.
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References
Li, T.: Computer Immunology. Publishing House of Electronics Industry, Beijing (2004)
Knight, J.C., Strunk, E.A., Sullivan, K.J.: Towards a Rigorous Definition of Information System Survivability. In: Proc. of DISCEX, pp. 78–89 (2003)
Linger, E.C., Lipson, H.F.: Requirements Definition for Survivable Network Systems. In: Proc. of ICRE (1998)
Richard, C.L., Howard, F.L., et al.: Life-Cycle Models for Survivable Systems. Technical Report CMU/SEI-2002-TR-026 (2002)
Westmark, V.R.: A Definition for Information System Survivability. In: Proc. of HICSS, pp. 303–312 (2004)
Zhang, Y.Q., Zhang, H.Z.: Analysis on characters of survivability and emergent algorithms. Journal on Communications 26(1), 124–128 (2005)
Li, T.: An immunity based network security risk estimation. Science in China Ser. F Information Sciences 48(5), 798–816 (2005)
Tedesco, G., Aickelin, U.: Data Reduction in Intrusion Alert Correlation. WSEAS Transactions on Computers 1(5), 186–193 (2006)
Madan, B.B., Goševa-Popstojanova, K., Vaidyanathan, K., et al.: Modeling and quantification of security attributes of software systems. In: Proc. of the International Conference on Dependable Systems and Networks, Washington, pp. 505–514 (2002)
Li, H., Cai, Z.M., Han, C.Z., Guan, X.H.: An Intrusion Detection Framework Based on Information Fusion. Mini-Micro Systems 24(9), 1602–1606 (2003)
Wang, Y.F., Li, T., et al.: A Real Time Method of Risk Evaluation Based on Artificial Immune System for Network Security. Acta Electronica Sinica 33(5), 945–949 (2005)
Kim, J., Bentley, P.J.: Towards an artificial immune system for network intrusion detection: an investigation of dynamic clonal selection. In: Proc. of the Congress on Evolutionary Computation, pp. 1015–1020 (2002)
Twycross, J., Aickelin, U.: Experimenting with innate immunity. In: Proc. of the Workshop on Artificial Immune Systems and Immune System Modelling, Bristol, pp. 18–19 (2006)
Harmer, P.K., Williams, P.D., Gunsch, G.H., et al.: An artificial immune system architecture for computer security applications. IEEE Transaction on Evolutionary Computation 6, 252–280 (2002)
Chen, X.Q., Zhang, J.H., Fu, L., et al.: Model for the Deliver of Essential Services in the Survivability Network System Based on Mobile Agent. Journal of Chongqing University 27(10), 37–39 (2004)
Li, T.: An immune based dynamic intrusion detection model. Chinese Science Bulletin 50(17), 1912–1919 (2005)
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© 2006 Springer-Verlag Berlin Heidelberg
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Zeng, J., Liu, X., Li, T., Sun, F., Peng, L., Liu, C. (2006). An Immune-Based Model for Service Survivability. In: Pointcheval, D., Mu, Y., Chen, K. (eds) Cryptology and Network Security. CANS 2006. Lecture Notes in Computer Science, vol 4301. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11935070_25
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DOI: https://doi.org/10.1007/11935070_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-49462-1
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