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Immunity and Mobile Agent Based Intrusion Detection for Grid

  • Xun Gong
  • Tao Li
  • Ji Lu
  • Tiefang Wang
  • Gang Liang
  • Jin Yang
  • Feixian Sun
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4088)

Abstract

This paper analyzes the distinctive characteristics of grid environments and proposes a novel immunity and mobile agent based intrusion detection for grid (IMIDG) model. Then, the concepts and formal definitions of self, nonself, antibody, antigen, agent and match algorithm in the grid security domain are given. Besides, the mathematical models of self, mature MoA (mature monitoring agent), dynamic memory MoA (memory monitoring agent) survival, CoA (communicator agent), and BoA (beating off agent) are established. The effects of several import parameters on system performance and detection efficiency in the model of dynamic memory MoA survival are analyzed and shown in the experiments. Our theoretical analysis and experimental results show the model which enhances detection efficiency and assures steady performance in immune-based IDS is a good solution to grid intrusion detection.

Keywords

False Negative Rate Intrusion Detection Mobile Agent Intrusion Detection System Artificial Immune System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Foster, C.K., Tsudik, G., Tuecke, S.: A Security Architecture for Computational Grids. In: Proc. of Computer and Communication Security (1998).Google Scholar
  2. 2.
    Leu, F.-Y., Lin, J.-C., Li, M.-C., Yang, C.-T.: A Performance-Based Grid Intrusion Detection System. In: Proc. of International Computer Software and Applications, vol. 1, pp. 525–530 (2005)Google Scholar
  3. 3.
    Tolba, M., Abdel-Wahab, M., Taha, I., Al-Shishtawy, A.: GIDA: Toward Enabling Grid Intrusion Detection Systems. In: Proc. of the Second International Intelligent Computing and Information Systems Conference (2005)Google Scholar
  4. 4.
    Forrest, S., Hofmeyr, S., Somayaji, A.: Computer Immunology. Proc. of Communications of the ACM 40, 88–96 (1997)CrossRefGoogle Scholar
  5. 5.
    Somayaji, A., Hofmeyr, S.A., Forrest, S.: Principles of a Computer Immune System. In: Proc. of the New Security Paradigms 1997, pp. 75–82 (1997)Google Scholar
  6. 6.
    Li, T.: Compute immunology. Publishing House of Electronics Industry, Beijing (2004)Google Scholar
  7. 7.
    Li, T.: A New Model for Dynamic Intrusion Detection. LNCS, pp. 72–84. Springer, Heidelberg (2005)Google Scholar
  8. 8.
    Li, T.: An immune based dynamic intrusion detection model. Chinese Science Bulletin, 2650–2657 (2005)Google Scholar
  9. 9.
    Li, T.: An immunity based network security risk estimation. Science in China Ser. F Information Sciences, pp. 557–578 (2005)Google Scholar
  10. 10.
    Li, T.: An Immune-Based Model for Computer Virus Detection. LNCS, pp. 59–71. Springer, Heidelberg (2005)Google Scholar
  11. 11.
    Dasgupta, D.: Immunity-based intrusion detection system: A general framework. In: Proc. of 22nd National Information Systems Security Conference, pp. 147–160 (1999)Google Scholar
  12. 12.
    Machado, R.B., Boukerche, A., Sobral, J.B.M., Juca, K.R.L., Notare, M.S.M.A.: A Hybird Artificial Immune and Mobile Agent Intrusion Detection Base Model for Computer Network Operations. In: Proc. of the 19th IEEE International Parallel and Distributed Processing (2005)Google Scholar
  13. 13.
    Harmer, P.K., Williams, P.D., Gunsch, G.H., Lamont, G.B.: An Artificial Immune System Architecture for Computer Security Applications. Proc. of IEEE Transactions on Evolutionary Computation 6 (2002)Google Scholar
  14. 14.
    Murshed, M., Buyya, R., Abramson, D.: GridSim: A Grid Simulation Toolkit for Resource Management and Scheduling in Large-Scale Grid Computing Environments. In: Proc. of the 17th IEEE International Symposium on Parallel and Distributed (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Xun Gong
    • 1
  • Tao Li
    • 1
  • Ji Lu
    • 1
  • Tiefang Wang
    • 1
  • Gang Liang
    • 1
  • Jin Yang
    • 1
  • Feixian Sun
    • 1
  1. 1.School of Computer ScienceSichuan Univ.ChengduChina

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