Skip to main content

Cooperative Automated Worm Response and Detection ImmuNe ALgorithm(CARDINAL) Inspired by T-Cell Immunity and Tolerance

  • Conference paper
Artificial Immune Systems (ICARIS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3627))

Included in the following conference series:

Abstract

The role of T-cells within the immune system is to confirm and assess anomalous situations and then either respond to or tolerate the source of the effect. To illustrate how these mechanisms can be harnessed to solve real-world problems, we present the blueprint of a T-cell inspired algorithm for computer security worm detection. We show how the three central T-cell processes, namely T-cell maturation, differentiation and proliferation, naturally map into this domain and further illustrate how such an algorithm fits into a complete immune inspired computer security system and framework.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aickelin, U., Bentley, P., Cayzer, S., Kim, J., McLeod, J.: Danger theory: The link between ais and ids. In: Timmis, J., Bentley, P.J., Hart, E. (eds.) ICARIS 2003. LNCS, vol. 2787, pp. 156–167. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  2. Aickelin, U., Greensmith, J., Twycross, J.: Immune system approaches to intrusion detection - a review. In: Nicosia, G., Cutello, V., Bentley, P.J., Timmis, J. (eds.) ICARIS 2004. LNCS, vol. 3239, pp. 316–329. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  3. Anagnostakis, K.G., Greenwald, M.B., Ioannidis, S., Keromytis, A.D., Li, D.: A cooperative immunization system for an untrusting internet. In: Proceedings of the 11th International Conference on Networks (ICON), Sydney (October 2003)

    Google Scholar 

  4. Bentley, P.J., Greensmith, J., Ujjin, S.: Two ways to grow tissue for artificial immune systems. In: Jacob, C., Pilat, M.L., Bentley, P.J., Timmis, J.I. (eds.) ICARIS 2005. LNCS, vol. 3627, pp. 139–152. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  5. Coico, R., Sunshine, G., Benjamini, E.: Immunology: A Short Course, 5th edn. John Wiley & Son, Chichester (2003)

    Google Scholar 

  6. Greensmith, J., Aickelin, U., Cayzer, S.: Introducing dendritic cells: A novel immune-inspired algorithm for anomaly detection. In: Jacob, C., Pilat, M.L., Bentley, P.J., Timmis, J.I. (eds.) ICARIS 2005. LNCS, vol. 3627, pp. 153–167. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  7. Janeway, C.A., Travers, P., Walport, M., Shlomchik, M.J.: Immunobiology: the immune system in health and disease, 6th edn. Garland Science Publishing (2005)

    Google Scholar 

  8. Kim, J.: Integrating Artificial Immune Algorithms for Intrusion Detection. PhD thesis, Department of Computer Science, University College London (2002)

    Google Scholar 

  9. Matzinger, P.: An innate sense of danger. Seminars in Immunology 10, 399–415 (1998)

    Article  Google Scholar 

  10. Moore, D., Paxson, V., Savage, S., Shannon, C., Staniford, S., Weaver, N.: Inside the slammer worm. IEEE Security and Privacy 1(4), 33–39 (2003)

    Article  Google Scholar 

  11. Moore, D., Shannon, C.: Code-red: a case study on the spread and victims of an internet worm. In: Proceedings of the 2002 ACM SIGCOMM Internet Measurement Workshop, Marseille, France, November 2002, pp. 273–284 (2002)

    Google Scholar 

  12. Nazario, J. (2005), http://www.wormblog.com

  13. Nojiri, D., Rowe, J., Levitt, K.: Cooperative response strategies for large scale attack mitigation. In: DARPA Information Survivability Conference and Exposition, pp. 293–302 (2003)

    Google Scholar 

  14. Porras, P., Briesemeister, L., Skinner, K., Levitt, K., Rowe, J., Ting, Y.A.: A hybrid quarantine defense. In: Proceedings of the 2004 ACM workshop on Rapid malcode (WORM 2004), Washington DC, USA, October 2004, pp. 73–82 (2004)

    Google Scholar 

  15. Twycross, J.: Soma - a self-orgnasing mobile agent immune system for computer networks. Unpublished working report (September 2004)

    Google Scholar 

  16. Weaver, N., Staniford, S., Paxson, V.: Very fast containment of scanning worms. In: Proceedings of the 13th Usenix Security Conference (2004)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Kim, J., Wilson, W.O., Aickelin, U., McLeod, J. (2005). Cooperative Automated Worm Response and Detection ImmuNe ALgorithm(CARDINAL) Inspired by T-Cell Immunity and Tolerance. In: Jacob, C., Pilat, M.L., Bentley, P.J., Timmis, J.I. (eds) Artificial Immune Systems. ICARIS 2005. Lecture Notes in Computer Science, vol 3627. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11536444_13

Download citation

  • DOI: https://doi.org/10.1007/11536444_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28175-7

  • Online ISBN: 978-3-540-31875-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics