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Realization of a self-recognition algorithm based on the biological immune system

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Abstract

As the use of the computer is popularized, the damage from computer viruses and hacking by malicious users is increasing rapidly. To block the hacking that is an intrusion into a person's computer, and the viruses that destroy data, a study into an intrusion detection and virus detection system based on the biological immune system is in progress. In this article, we describe a model of positive and negative selection for self-recognition, which has a similar function to the cytotoxic T cells that play an important role in the biological immune system. We propose a self/nonself discrimination algorithm for a computer system, which will the important when we detect data infected by a computer virus, of data modified by an intrusion from outside. We also show the validity and effectiveness of the proposed self-recognition algorithm by a computer simulation of some infected data obtained from cell changes and string changes in the self-file.

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References

  1. Hofmeyr S, Forrest S, Somayaji A (1998) Intrusion detection using sequences of system calls. J Comput Secur 6:151–180

    Google Scholar 

  2. Warrender C, Forrest S, Pearlmutter B (1999) Detecting intrusions using system calls: alternative data models. Proceedings of the IEEE Symposium on Security and Privacy. IEEE Computer Society, Oakland, pp 133–145

    Google Scholar 

  3. Dasgupta D (2000) An immune agent architecture for intrusion detection. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2000) Workshop Program. Morgan Kaufmann, Las Vegas, pp 42–44

    Google Scholar 

  4. Gu JB, Lee DW, Park SH, et al. (2000) An immunity-based security layer model. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2000) Workshop Program. Morgan Kaufmann, Las Vegas, pp 47–48

    Google Scholar 

  5. Gu JB, Lee DW, Sim KB, et al. (2000) An antibody layer for internet security. Proceedings of the Global Telecommunication Conference (GLOBECOM 2000). IEEE Communications Society, San Francisco, pp 450–454

    Google Scholar 

  6. Gu JB, Lee DW, Sim KB, et al. (2000) An immunity based security layer against internet antigens. Trans IEICE, E83-B (11):2570–2575

    Google Scholar 

  7. Forrest S, Perelson AS, Allen L, et al. (1994) Self-nonself discrimination in a computer. Proceedings of the 1994 IEEE Symposium on Research in Security and Privacy, IEEE Computer Society, Oakland, pp 202–212

  8. Harmer P, Lamont G (2000) An agent-based architecture for a computer virus immune system. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2000) Workshop Program. Morgan Kaufmann, Las Vegas, pp 45–46

    Google Scholar 

  9. Roitt I, Brostoff J, Male D (1996) Immunology, 4th ed, Mosby

  10. Wallace RA, Sanders GP, Ferl RJ (1991) Biology: the science of life, 3rd edn. HarperCollins

  11. Somayaji A, Hofmeyr S, Forrest S (1998) Principles of a computer immune system. Proceedings of the New Security Paradigms Workshop. IEEE Computer Society, Rhode Island, pp 75–82

    Google Scholar 

  12. Forrest S, Hofmeyr S, Somayaji A (1997) Computer immunology. Communi ACM 40(10):88–96

    Article  Google Scholar 

  13. D'haeseleer P, Forrest S, Helman P (1996) An immunological approach to change detection: algorithms, analysis, and implications. Proceedings of the IEEE Symposium on Computer Security and Privacy. IEEE Computer Society, Oakland, pp 110–119

    Google Scholar 

  14. Dasgupta D, Forrest S (1999) An anomaly-detection algorithm inspired by the immune system. Artificial immune systems and their applications. Springer, Berlin Heidelberg, pp 262–276

    Google Scholar 

Download references

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Correspondence to K. -B. Sim.

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Sim, K.B., Sun, S.J. & Lee, D.W. Realization of a self-recognition algorithm based on the biological immune system. Artif Life Robotics 7, 32–39 (2003). https://doi.org/10.1007/BF02480883

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  • DOI: https://doi.org/10.1007/BF02480883

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