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The Intrusion Detection Model of Multi-dimension Data Based on Artificial Immune System

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Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems (AsiaSim 2016, SCS AutumnSim 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 646))

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Abstract

Facing to the security of the data, this paper proposes a new intrusion detection model in high dimensional data environment based on the artificial immune system. This model pre-processes the high dimensional data to build the data set of self and non-self. In order to make the detectors more efficient and reliable, we improve the existing negative selection algorithm by adding the means of shift mutation and random grouping. Meanwhile, the adaptive learning and dynamic updating of the detectors are realized by introducing the evolutionary computation. The experimental results show that the proposed model can detect the data of non-self and identify the self-data effectively.

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Acknowledgment

This work was supported in part by the Key Project of the National Natural Science Foundation of China (no. 61134009), the National Natural Science Foundation of China (nos. 61473077, 61473078), Program for Changjiang Scholars from the Ministry of Education, Specialized Research Fund for Shanghai Leading Talents, and Project of the Shanghai Committee of Science and Technology (no. 13JC1407500).

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Authors and Affiliations

  1. Engineering Research Center of Digitized Textile & Apparel Technology, Ministry of Education, Shanghai, China

    Lihong Ren & Yongsheng Ding

  2. College of Information Science and Technology, Donghua University, Shanghai, 201620, China

    Weikai Wang, Lihong Ren & Yongsheng Ding

Authors
  1. Weikai Wang
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  2. Lihong Ren
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  3. Yongsheng Ding
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Corresponding author

Correspondence to Lihong Ren .

Editor information

Editors and Affiliations

  1. Beihang University , Beijing, China

    Lin Zhang

  2. Beihang University , Beijing, China

    Xiao Song

  3. Beihang University , Beijing, China

    Yunjie Wu

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Wang, W., Ren, L., Ding, Y. (2016). The Intrusion Detection Model of Multi-dimension Data Based on Artificial Immune System. In: Zhang, L., Song, X., Wu, Y. (eds) Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems. AsiaSim SCS AutumnSim 2016 2016. Communications in Computer and Information Science, vol 646. Springer, Singapore. https://doi.org/10.1007/978-981-10-2672-0_16

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  • DOI: https://doi.org/10.1007/978-981-10-2672-0_16

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2671-3

  • Online ISBN: 978-981-10-2672-0

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