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International Symposium on Neural Networks

ISNN 2005: Advances in Neural Networks – ISNN 2005 pp 409–414Cite as

Building an Intrusion Detection System Based on Support Vector Machine and Genetic Algorithm

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3498))

Abstract

Host-based Intrusion Detection System (IDS) utilizes the log files as the data source and is limited by the content of the log files. If the log files were tampered, the IDS cannot accurately detect illegal behaviors. Therefore, the proposed IDS for this paper will create its own data source file. The system is controlled by the Client program and Server program. The client program is responsible for recording a user’s behavior in the data source file. The data source file is then transmitted to the server program, which will send it to SVM to be analyzed. The analyzed result will then be transmitted back to the client program. The client program will then decide on the course of actions to take based on the analyzed result. Also, the genetic algorithm is used to optimize information to extract from the data source file so that detection time can be optimized.

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References

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Author information

Authors and Affiliations

  1. Department of Logistics Engineering and Management, National Taichung Institute of Technology,  

    Rongchang Chen

  2. Department of Computer Science and Information Management, Hungkuang University, Taichung, 433, Taiwan, China

    Jeanne Chen

  3. Department of Information Management, National Taichung Institute of Technology, No. 129, Sec. 3, Sanmin Rd., Taichung, 404, Taiwan, China

    Tungshou Chen, Chunhung Hsieh & Kaiyang Wu

  4. Department of Information Management, Hsiuping Institute of Technology, No.11, Gungye Rd., Dali City, Taichung, 412, Taiwan, China

    Teyu Chen

Authors
  1. Rongchang Chen
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  2. Jeanne Chen
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  3. Tungshou Chen
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  4. Chunhung Hsieh
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  5. Teyu Chen
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  6. Kaiyang Wu
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. The Key Laboratory of Optoelectric Technology & Systems, Ministry of Education, China

    Xiao-Feng Liao

  3. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

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© 2005 Springer-Verlag Berlin Heidelberg

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Cite this paper

Chen, R., Chen, J., Chen, T., Hsieh, C., Chen, T., Wu, K. (2005). Building an Intrusion Detection System Based on Support Vector Machine and Genetic Algorithm. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3498. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427469_66

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  • DOI: https://doi.org/10.1007/11427469_66

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25914-5

  • Online ISBN: 978-3-540-32069-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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