Skip to main content
SpringerLink
Log in

Immuno-inspired Knowledge Management for Ad Hoc Wireless Networks

  • Chapter
Smart Information and Knowledge Management

Part of the book series: Studies in Computational Intelligence ((SCI,volume 260))

Abstract

During the last years approaches inspired by biological immune systems showed promising results in the field of misbehavior detection and classification of data in general. In this chapter we give a comprehensive overview on the recent developments in the area of biologically inspired classification approaches of possible threats and misbehavior, especially in the area of ad hoc networks. We discuss numerous immuno related approaches, such as negative selection, B-cell cloning, Dendritic cell algorithm or Danger signals. We review present approaches and address their applicability to ad hoc networks. We further discuss challenges in translating functionality of the biological immune system to technical systems.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover 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. Szor, P.: The art of computer virus research and defense. Addison-Wesley Professional, Reading (2005)

    Google Scholar 

  2. Drozda, M., Schildt, S., Schaust, S., Einhellinger, S., Szczerbicka, H.: A tool for prototyping AIS based protection systems for ad hoc and sensor networks. Cybernetics and Systems 39(7), 719–742 (2008)

    Article  MATH  Google Scholar 

  3. Murphy, K.P., Travers, P., Walport, M.: Janeway’s immunobiology. Garland Pub. (2008)

    Google Scholar 

  4. Banchereau, J., Briere, F., Caux, C., Davoust, J., Lebecque, S., Liu, Y.J., Pulendran, B., Palucka, K.: Immunobiology of dendritic cells. Annual review of immunology 18(1), 767–811 (2000)

    Article  Google Scholar 

  5. Matzinger, P.: Tolerance, danger, and the extended family. Annual Review of Immunology 12(1), 991–1045 (1994)

    Google Scholar 

  6. Whitaker, L., Renton, A.M.: On the plausibility of the clonal expansion theory of the immune system in terms of the conbinatorial possibilities of amino-acids in antigen and self-tolerance. Journal of theoretical biology 164(4), 531–536 (1993)

    Article  Google Scholar 

  7. Campbell, N., Reece, J., Markl, J.: Biologie, 6. überarbeitete Auflage (2006)

    Google Scholar 

  8. D’haeseleer, P., Forrest, S., Helman, P.: An Immunological Approach to Change Detection: Algorithms, Analysis and Implications. In: IEEE Symposium on Security and Privacy, pp. 110–119 (1996)

    Google Scholar 

  9. Timmis, J., Hone, A., Stibor, T., Clark, E.: Theoretical advances in artificial immune systems. Theor. Comput. Sci. 403(1), 11–32 (2008)

    Article  MATH  MathSciNet  Google Scholar 

  10. Ji, Z., Dasgupta, D.: Applicability issues of the real-valued negative selection algorithms. In: Proc. of the 8th annual conference on Genetic and evolutionary computation, pp. 111–118 (2006)

    Google Scholar 

  11. Kelsey, J., Timmis, J.: Immune Inspired Somatic Contiguous Hypermutation for Function Optimisation. In: Cantú-Paz, E., et al. (eds.) GECCO 2003. LNCS, vol. 2723, pp. 207–218. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  12. Aickelin, U., Bentley, P.J., 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. 147–155. Springer, Heidelberg (2003)

    Google Scholar 

  13. Greensmith, J., Aickelin, U., Cayzer, S.: Introducing Dendritic Cells as 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)

    Google Scholar 

  14. Perkins, C.E., Royer., E.M.: Ad hoc On-Demand Distance Vector Routing.. In: Proc. of the 2nd IEEE Workshop on Mobile Computing Systems and Applications, pp. 90–100 (1999)

    Google Scholar 

  15. IEEE Std. 802.11: Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications. IEEE Standard for Information technology

    Google Scholar 

  16. Feeney, L.M., Nilsson, M.: Investigating the energy consumption of a wireless network interface in an ad hoc networking environment. In: Proc. of Twentieth Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM), vol. 3, pp. 1548–1557 (2001)

    Google Scholar 

  17. Iren, S., Amer, P.D., Conrad, P.T.: The transport layer: tutorial and survey. ACM Computing Surveys (CSUR) 31(4), 360–404 (1999)

    Article  Google Scholar 

  18. Marti, S., Giuli, T.J., Lai, K., Baker, M.: Mitigating routing misbehavior in mobile ad hoc networks. In: Proc. of International Conference on Mobile Computing and Networking, pp. 255–265 (2000)

    Google Scholar 

  19. Kyasanur, P., Vaidya, N.H.: Detection and handling of mac layer misbehavior in wireless networks. In: Proceedings of the International Conference on Dependable Systems and Networks, pp. 173–182 (2002)

    Google Scholar 

  20. Jakobsson, M., Wetzel, S., Yener, B.: Stealth attacks on ad-hoc wireless networks. In: Proc. of 2003 IEEE 58th Vehicular Technology Conference (VTC Fall), vol. 3, pp. 2103–2111 (2003)

    Google Scholar 

  21. Savage, S., Wetherall, D., Karlin, A., Anderson, T.: Network support for ip traceback. IEEE/ACM Trans. Netw. 9(3), 226–237 (2001)

    Article  Google Scholar 

  22. Yang, H., Meng, X., Lu, S.: Self-organized network-layer security in mobile ad hoc networks. In: WiSE 2002: Proceedings of the 1st ACM workshop on Wireless security, pp. 11–20. ACM, New York (2002)

    Chapter  Google Scholar 

  23. Sun, B., Wu, K., Pooch, U.W.: Alert aggregation in mobile ad hoc networks. In: WiSe 2003: Proceedings of the 2nd ACM workshop on Wireless security, pp. 69–78. ACM, New York (2003)

    Chapter  Google Scholar 

  24. Padmanabhan, V.N., Simon, D.R.: Secure traceroute to detect faulty or malicious routing. SIGCOMM Comput. Commun. Rev. 33(1), 77–82 (2003)

    Article  Google Scholar 

  25. Hu, Y.C., Perrig, A., Johnson, D.B.: Ariadne: a secure on-demand routing protocol for ad hoc networks. In: MobiCom 2002: Proceedings of the 8th annual international conference on Mobile computing and networking, pp. 12–23. ACM, New York (2002)

    Chapter  Google Scholar 

  26. Douceur, J.R.: The sybil attack. In: IPTPS 2001: Revised Papers from the First International Workshop on Peer-to-Peer Systems, London, UK, pp. 251–260. Springer, Heidelberg (2002)

    Google Scholar 

  27. Hu, Y.C., Perrig, A., Johnson, D.B.: Rushing attacks and defense in wireless ad hoc network routing protocols. In: WiSe 2003: Proceedings of the 2nd ACM workshop on Wireless security, pp. 30–40. ACM, New York (2003)

    Chapter  Google Scholar 

  28. Hu, Y.C., Perrig, A., Johnson, D.: Packet leashes: a defense against wormhole attacks in wireless networks. In: Proc. of Twenty-Second Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM), vol. 3, pp. 1976–1986 (2003)

    Google Scholar 

  29. Juels, A., Brainard, J.: Client puzzles: A cryptographic countermeasure against connection depletion attacks. In: Kent, S. (ed.) NDSS 1999: Networks and Distributed Security Systems, pp. 151–165 (1999)

    Google Scholar 

  30. Savage, S., Cardwell, N., Wetherall, D., Anderson, T.: Tcp congestion control with a misbehaving receiver. SIGCOMM Comput. Commun. Rev. 29(5), 71–78 (1999)

    Article  Google Scholar 

  31. Aad, I., Hubaux, J.P., Knightly, E.W.: Denial of service resilience in ad hoc networks. In: MobiCom 2004: Proceedings of the 10th annual international conference on Mobile computing and networking, pp. 202–215. ACM, New York (2004)

    Chapter  Google Scholar 

  32. Hofmeyr, S.A., Forrest, S.: Immunity by design: An artificial immune system. In: Proc. of Genetic and Evolutionary Computation Conference (GECCO), vol. 2, pp. 1289–1296 (1999)

    Google Scholar 

  33. Sarafijanovic, S., Le Boudec, J.Y.: An artificial immune system for misbehavior detection in mobile ad-hoc networks with virtual thymus, clustering, danger signal and memory detectors. In: Proc. of International Conference on Artificial Immune Systems (ICARIS), pp. 342–356 (2004)

    Google Scholar 

  34. Sarafijanovic, S., Le Boudec, J.Y.: An artificial immune system approach with secondary response for misbehavior detection in mobile ad hoc networks. IEEE Transactions on Neural Networks 16(5), 1076–1087 (2005)

    Article  Google Scholar 

  35. Drozda, M., Schaust, S., Szczerbicka, H.: Is AIS Based Misbehavior Detection Suitable for Wireless Sensor Networks?. In: Proc. of IEEE Wireless Communications and Networking Conference (WCNC 2007), pp. 3130–3135 (2007)

    Google Scholar 

  36. Drozda, M., Schaust, S., Szczerbicka, H.: AIS for Misbehavior Detection in Wireless Sensor Networks: Performance and Design Principles. In: Computing Research Repository (CoRR) (2009) arXiv.org/abs/0906.3461

    Google Scholar 

  37. Drozda, M., Schildt, S., Schaust, S.: An Immuno-Inspired Approach to Fault and Misbehavior Detection in Ad Hoc Wireless Networks. Technical report, Leibniz University of Hannover (2009)

    Google Scholar 

  38. Schaust, S., Drozda, M.: Influence of Network Payload and Traffic Models on the Detection Performance of AIS. In: Proc. of International Symposium on Performance Evaluation of Computer and Telecommunication Systems (SPECTS 2008), pp. 44–51 (2008)

    Google Scholar 

  39. Barr, R., Haas, Z., Renesse, R.: Scalable wireless ad hoc network simulation. In: Handbook on Theoretical and Algorithmic Aspects of Sensor, Ad hoc Wireless, and Peer-to-Peer Networks, pp. 297–311 (2005)

    Google Scholar 

  40. Bokareva, T., Bulusu, N., Jha, S.: Sasha: toward a self-healing hybrid sensor network architecture. In: EmNets 2005: Proceedings of the 2nd IEEE workshop on Embedded Networked Sensors, Washington, DC, USA, pp. 71–78. IEEE Computer Society, Los Alamitos (2005)

    Chapter  Google Scholar 

  41. Mazhar, N., Farooq, M.: BeeAIS: Artificial immune system security for nature inspired, MANET routing protocol, BeeAdHoc. In: de Castro, L.N., Von Zuben, F.J., Knidel, H. (eds.) ICARIS 2007. LNCS, vol. 4628, pp. 370–381. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  42. Kim, J., Bentley, P.J., Wallenta, C., Ahmed, M., Hailes, S.: Danger Is Ubiquitous: Detecting Malicious Activities in Sensor Networks Using the Dendritic Cell Algorithm. In: Bersini, H., Carneiro, J. (eds.) ICARIS 2006. LNCS, vol. 4163, pp. 390–403. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  43. Kohavi, R., John, G.H.: Wrappers for feature subset selection. Artificial Intelligence 97(1-2), 273–324 (1997)

    Article  MATH  Google Scholar 

  44. Anantvalee, T., Wu, J.: A survey on intrusion detection in mobile ad hoc networks. Wireless/Mobile Network Security, 159–180 (2007)

    Google Scholar 

  45. Mishra, A., Nadkarni, K., Patcha, A.: Intrusion detection in wireless ad hoc networks. IEEE Wireless Communications 11(1), 48–60 (2004)

    Article  Google Scholar 

  46. Zhang, Y., Lee, W., Huang, Y.A.: Intrusion Detection Techniques for Mobile Wireless Networks. Wireless Networks 9(5), 545–556 (2003)

    Article  Google Scholar 

  47. Davoudani, D., Hart, E., Paechter, B.: Computing the state of specknets: Further analysis of an innate immune-inspired model. In: Bentley, P.J., Lee, D., Jung, S. (eds.) ICARIS 2008. LNCS, vol. 5132, pp. 95–106. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  48. Atakan, B., Akan, O.B.: Immune system based distributed node and rate selection in wireless sensor networks. In: BIONETICS 2006: Proceedings of the 1st international conference on Bio inspired models of network, information and computing systems, p. 3. ACM, New York (2006)

    Chapter  Google Scholar 

  49. Albergante, L.: Wireless discussion forums: Automatic management via artificial immune systems. In: Proc. of International Symposium on Performance Evaluation of Computer and Telecommunication Systems (SPECTS), pp. 74–81 (2008)

    Google Scholar 

  50. Barrett, C., Drozda, M., Marathe, M.V., Marathe, A.: Characterizing the interaction between routing and MAC protocols in ad-hoc networks. In: Proc. of the 3rd ACM international symposium on Mobile ad hoc networking and computing (Mobihoc), pp. 92–103 (2002)

    Google Scholar 

  51. Drozda, M., Schaust, S., Schildt, S., Szczerbicka, H.: An Error Propagation Algorithm for Ad Hoc Wireless Networks. In: Andrews, P.S. (ed.) ICARIS 2009. LNCS, vol. 5666, pp. 260–273. Springer, Heidelberg (2009)

    Google Scholar 

  52. Alpaydin, E.: Introduction To Machine Learning. MIT Press, Cambridge (2004)

    Google Scholar 

  53. Jung, H.W., Tschaplinski, T.J., Wang, L., Glazebrook, J., Greenberg, J.T.: Priming in Systemic Plant Immunity. Science 324(5923), 89–91 (2009)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Simulation and Modeling Group, Dept. of Computer Science, Leibniz University of Hannover, Welfengarten 1, 30167, Hannover, Germany

    Martin Drozda, Sven Schaust & Helena Szczerbicka

Authors
  1. Martin Drozda
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sven Schaust
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Helena Szczerbicka
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Faculty of Management and Economics, Gdansk University of Technology, Str.Narutowicza 11/12, 80-233, Gdansk, Poland

    Edward Szczerbicki

  2. Institute of Informatics, Wroclaw University of Technology, Str.Wyb.Wyspianskiego 27, 50-370, Wroclaw, Poland

    Ngoc Thanh Nguyen

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Drozda, M., Schaust, S., Szczerbicka, H. (2010). Immuno-inspired Knowledge Management for Ad Hoc Wireless Networks. In: Szczerbicki, E., Nguyen, N.T. (eds) Smart Information and Knowledge Management. Studies in Computational Intelligence, vol 260. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04584-4_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-04584-4_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04583-7

  • Online ISBN: 978-3-642-04584-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation