Advertisement

Immunity and Mobile Agent Based Grid Intrusion Detection

  • Xun Gong
  • Tao Li
  • Gang Liang
  • Tiefang Wang
  • Jin Yang
  • Xiaoqin Hu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4115)

Abstract

This paper analyzes the unique characteristics of a grid environment and the deficiencies of current grid intrusion detection systems, and proposes a novel immunity and mobile agent based grid intrusion detection (IMGID) model. Then, the concepts and formal definitions of self, nonself, antibody, antigen and agent in the grid security domain are given. Furthermore, the mathematical models of self, mature MoA (mature monitoring agent) and dynamic memory MoA (memory monitoring agent) survival are established. Our theoretical analysis and experimental results show that the model is a good solution to grid intrusion detection.

Keywords

Intrusion Detection Training Time 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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Foster, Kesselman, C., 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.
    De Castro, L.N., Timmis, J.I.: Artificial Immune Systems as a Novel Soft Computing Paradigm. Soft Computing journal 7, 526–544 (2003)Google Scholar
  4. 4.
    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
  5. 5.
    Forrest, S., Hofmeyr, S., Somayaji, A.: Computer Immunology. In: Proc. of Communications of the ACM, vol. 40, pp. 88–96 (1997)Google Scholar
  6. 6.
    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
  7. 7.
    Li, T.: Compute immunology. Publishing House of Electronics Industry, Beijing (2004)Google Scholar
  8. 8.
    Li, T.: A New Model for Dynamic Intrusion Detection. LNCS, pp. 72–84. Springer, Heidelberg (2005)Google Scholar
  9. 9.
    Li, T.: An Immune based Dynamic Intrusion Detection Model. Chinese Science Bulletin, 2650–2657 (2005)Google Scholar
  10. 10.
    Li, T.: An Immunity based Network Security Risk Estimation. Science in China Ser. F Information Sciences, 557–578 (2005)Google Scholar
  11. 11.
    Li, T.: An Immune-Based Model for Computer Virus Detection. LNCS, pp. 59–71. Springer, Heidelberg (2005)Google Scholar
  12. 12.
    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
  13. 13.
    Machado, R.B., Boukerche, A., Sobral, J.B.M., Juca, K.R.L., Notare, M.S.M.A.: A Hybrid 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
  14. 14.
    Lin, J., Wang, C., Gou, Y.: Agent-based Access Control Security in Grid computing Environment. In: Proc. of Networking, Sensing and Control (2005)Google Scholar
  15. 15.
    Paul, K.H., Paul, D.W., Gregg, H.G., Gary, B.L.: An Artificial Immune System Architecture for Computer Security Applications. In: Proc. of IEEE Transactions on Evolutionary Computation, vol. 6 (2002)Google Scholar
  16. 16.
    Paul, K.H., Paul, D.W., Gregg, H.G., Gary, B.L.: An Artificial Immune System Architecture for Computer Security Applications. In: Proc. of IEEE Transaction on Evolutionary Computation, vol. 6, pp. 252–280 (2002)Google Scholar
  17. 17.
    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
  • Gang Liang
    • 1
  • Tiefang Wang
    • 1
  • Jin Yang
    • 1
  • Xiaoqin Hu
    • 1
  1. 1.School of Computer ScienceSichuan Univ.ChengduChina

Personalised recommendations