A Computer Security Model of Imitated Nature Immune and Its FSM

  • Zhenpeng Liu
  • Ailan Li
  • Dongfang Wang
  • Wansheng Tang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4688)


According to the nature immunology, This paper describe a computer security model imitated the principle of nature immunity, GECISM (GEneral Computer Immune System Model). The model is structured by agents. The agent imitates the immune cells. Through rules and co-operation the agent discriminate “self” and “non-self”. Further it eliminates “non-self”. The FSM model of GECISM accurately describes this system and meanwhile is the basement of performance analysis and system test about GECISM.


Artificial Immune System Primary Immune Response Immune Molecule Nature Immune System Information 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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Tong, J.-Y.: The Medicine Immunity and Microbiology, 3rd edn. The Press of People Health, Beijing (1996)Google Scholar
  2. 2.
    Hofmeyr, A., Forrest, S.: Architecture for an Artificial Immune System. Evolutionary Computation 1, 45–68 (2000)Google Scholar
  3. 3.
    Somayaji, A.B.:Operating System Stability and Security through Process Homeostasis. Albuquerque, The University of New Mexico, New Mexico (2002)Google Scholar
  4. 4.
    Warrander, C.: Effective Feedback in the Immune System. In: Genetic and Evolutionary Computation Conference Workship Program, pp. 329–332. Morgan Kaufman, San Francisco (2001)Google Scholar
  5. 5.
    Chao, D.L., Forrest, S.: Information Immune Systems. In: ICARIS. Proceedings of the First International Conference on Artificial Immune Systems (2002)Google Scholar
  6. 6.
    Balthrop, J., Esponda, F., Forrest, S.(eds.): Coverage and Generalization in an Artificial Immune System. In: GECCO 2002. Proceedings of the Genetic and Evolutionary Computation Conference, Morgan Kaufmann, New York (2002)Google Scholar
  7. 7.
    Forrest, S., Hofmeyr, S., Somayaji, A.: Computer Immunology. Communications of the ACM 10, 88–96 (1997)CrossRefGoogle Scholar
  8. 8.
    Forrest, S., Perelson, A., Allen, L.(eds.): Self-Nonself Discrimination in a Computer. In: Proceedings of the 1994 IEEE Symposium on Research in Security and Privacy, pp. 202–212. IEEE Computer Society Press, Los Alamitos (1994)Google Scholar
  9. 9.
    Liu, M., Ling, T.W.: A Data Model for Semistructured Data with Partial and Inconsistent Information. In: Zaniolo, C., Grust, T., Scholl, M.H., Lockemann, P.C. (eds.) EDBT 2000. LNCS, vol. 1777, pp. 27–31. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  10. 10.
    Steven, A., Hofmeyr, S., Forrest, S.: Immunity by Design: An Artificial for Immune System. In: GECCO. Proceedings of the l999 Genetic and Evolutionary Computation Conference, pp. 1289–1296 (1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Zhenpeng Liu
    • 1
    • 3
  • Ailan Li
    • 2
  • Dongfang Wang
    • 1
  • Wansheng Tang
    • 3
  1. 1.Network Center, Hebei University, 071002 BaodingChina
  2. 2.Department of Foundation Teaching, Hebei Jiaotong, Vocational & TechnicalCollege, 050091 ShijiazhuangChina
  3. 3.Institute of System Engineering, Tianjin University, 300072 TianjinChina

Personalised recommendations