Skip to main content
Springer Nature Link
Log in

Improving the Generalization Capability of Hybrid Immune Detector Maturation Algorithm

  • Conference paper
Hybrid Artificial Intelligent Systems (HAIS 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7208))

Included in the following conference series:

Abstract

In this work, an augmented hybrid immune detector maturation algorithm applied in anomaly detection is proposed to improve the generalization capability. Experiment results show the algorithm is more effective and its generalization capability to detect more similar patterns is improved.

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

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.

Similar content being viewed by others

References

  1. Corchado, E., Abraham, A., Carvalho, A.: Hybrid intelligent algorithms and applications. Information Sciences 180(14), 2633–2634 (2010)

    Article  MathSciNet  Google Scholar 

  2. Hart, E., Timmis, J.: Application areas of AIS: The past, the present and the future. Journal of Applied Soft Computing 8(1), 191–201 (2008)

    Article  Google Scholar 

  3. Timmis, J., et al.: An interdisciplinary perspective on artificial immune systems. Evolutionary Intelligence 1(1), 5–26 (2008)

    Article  Google Scholar 

  4. Greensmith, J., Aickelin, U., et al.: Information Fusion for Anomaly Detection with the Dendritic Cell Algorithm. Information Fusion 11(1), 21–34 (2010)

    Article  Google Scholar 

  5. Hofmeyr, S.A.: An Immunological Model of Distributed Detection and its Application to Computer Security, PhD Dissertation. University of New Mexico (1999)

    Google Scholar 

  6. Chen, J., et al.: Hybrid Immune Detector Maturation Algorithm with LifeCycle Model. In: International Conference on Computer Science and its Applications, pp. 213–218 (2009)

    Google Scholar 

  7. de Castro, L.N., et al.: Learning and Optimization Using the Clonal Selection Principle. IEEE Transactions on Evolutionary Computation 6(3), 239–251 (2002)

    Article  Google Scholar 

  8. Dougherty, J., Kohavi, R., Sahami, M.: Supervised and unsupervised discretization of continuous features, http://robotics.stanford.edu/~ronnyk/disc.ps

Download references

Author information

Authors and Affiliations

  1. Electronic Information Department, Zhejiang Wanli University, No.8 South Qian Hu Road, Ningbo, Zhejiang, 315100, China

    Jungan Chen, Feng Liang & Zhaoxi Fang

Authors
  1. Jungan Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Feng Liang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zhaoxi Fang
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Universidad de Salamanca, Plaza de la Merced S/N, 37008, Salamanca, Spain

    Emilio Corchado

  2. VŠB-TU Ostrava 17, Listopadu 15, 70833, Ostrava, Czech Republic

    Václav Snášel

  3. Machine Intelligence Research Labs(MIR Labs), Scientific Network for Innovation and Research Excellence, P.O. Box 2259, 98071, Auburn, Washington, USA

    Ajith Abraham

  4. Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland

    Michał Woźniak

  5. University of the Basque Country, Pº Manuel Lardizabal 1, 20018, San Sebastian, Spain

    Manuel Graña

  6. Yonsei University, 134 Shinchon-dong, Sudaemoon-ku, 120-749, Seoul, Korea

    Sung-Bae Cho

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Chen, J., Liang, F., Fang, Z. (2012). Improving the Generalization Capability of Hybrid Immune Detector Maturation Algorithm. In: Corchado, E., Snášel, V., Abraham, A., Woźniak, M., Graña, M., Cho, SB. (eds) Hybrid Artificial Intelligent Systems. HAIS 2012. Lecture Notes in Computer Science(), vol 7208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28942-2_27

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-28942-2_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28941-5

  • Online ISBN: 978-3-642-28942-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation