Formal Neuro-Immune Network

  • Alexander Tarakanov
  • Georgy Penev
  • Kurosh Madani
Conference paper
Part of the Advances in Soft Computing book series (AINSC, volume 19)


The paper presents an attempt to introduce a new formal notion of Neuro-Immune Network (NIN) based on a rigorous mathematical basis. This notion is inspired by a biological phenomenon of reciprocal impact between the neural and immune systems. The paper considers examples of NIN including a possible application to intrusion detection in computer networks.


Singular Value Decomposition Intrusion Detection Artificial Immune System Formal Protein Shape Space 
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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  1. 1.
    Ader R, Felten D, Cohen N (eds) (2000) Psycho-neuro-immunology. Academic Press, New YorkGoogle Scholar
  2. 2.
    Bay SD (1999) The UCI KDD archive []. University of California, Dept. of Information and Computer Science, Irvine, CAGoogle Scholar
  3. 3.
    Chebira A, Madani K, Mercier G (1997) Multi-neural networks hardware and software architecture: application to divide to simplify paradigm DTS. LNCS Vol. 1240, Springer Verlag, 1977, pp. 841–850.Google Scholar
  4. 4.
    Dasgupta D. (1999) Artificial Immune Systems and their Applications. Springer.Google Scholar
  5. 5.
    DeBoer RJ, Segel LA, Perelson AS (1992) Pattern formation in one and two-dimensional shape space models of the immune system. J Theoret Biol 155: 295–333CrossRefGoogle Scholar
  6. 6.
    Hori T, et al. (1995) The autonomic nervous system as a communication channel between the brain and the immune system. Neuroimmunomodulation 2: 203–215CrossRefGoogle Scholar
  7. 7.
    Horn R, Johnson C (1986) Matrix analysis. Cambridge University PressGoogle Scholar
  8. 8.
    Jerne NK (1974) Towards a network theory of the immune system. Ann Immunol (Inst. Pasteur) 125C: 373–389Google Scholar
  9. 9.
    Krogh A, Vedelsby J, Neural network ensembles, cross validation, and active learning. In: Tesauro G (ed) Advances in neural information processing systems 7. MIT Press, pp 231–238Google Scholar
  10. 10.
    Tarakanov A (1999) Formal peptide as a basic agent of immune networks: from natural prototype to mathematical theory and applications. In: Proc. 1st int. workshop of central and eastern Europe on multi-agent systems (CEEMAS’99). St.Petersburg, Russia, pp 281–292Google Scholar
  11. 11.
    Tarakanov AO (2001) Information security with formal immune networks. In: Gorodetsky VI, Skormin VA, Popyack LJ (eds) Information Assurance in Computer Networks (Lecture Notes in Computer Science). Springer, Berlin, pp 115–126CrossRefGoogle Scholar
  12. 12.
    Tarakanov A, Dasgupta D (2000) A formal model of an artificial immune system. Bio-Systems 55 (1–3): 151–158CrossRefGoogle Scholar
  13. 13.
    Tarakanov A, Skormin V (2002) Pattern recognition by immunocomputing (accepted to the 2002 Congress on Evolutionary Computation. Honolulu, USA )Google Scholar
  14. 14.
    Wasserman P (1990) Neural computing. Theory and practice. Van Nostrand Reihold, New YorkGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Alexander Tarakanov
    • 1
  • Georgy Penev
    • 1
  • Kurosh Madani
    • 2
  1. 1.St.Petersburg Institute for InformaticsAutomation of Russian Academy of Sciences (SPIIRAS)St-PetersburgRussia
  2. 2.Intelligence in Instrumentation and Systems Lab. (I2S) — SENART Institute of TechnologyUniversity PARIS XIILieusaintFrance

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