Research Output
Evaluation on multivariate correlation analysis based denial-of-service attack detection system
  In this paper, a Denial-of-Service (DoS) attack detection system is explored, where a multivariate correlation analysis technique based on Euclidean distance is applied for network traffic characterization and the principal of anomaly-based detection is employed in attack recognition. The effectiveness of the detection system is evaluated on the KDD Cup 99 dataset and the influence of data normalization on the performance of attack detection is analyzed in this paper as well. The evaluation results and comparisons prove that the detection system is effective in distinguishing DoS attack network traffic from legitimate network traffic and outperforms two state-of-the-art systems

  • Date:

    17 August 2012

  • Publication Status:

    Published

  • Publisher

    ACM Press

  • DOI:

    10.1145/2490428.2490450

  • Library of Congress:

    QA75 Electronic computers. Computer science

  • Dewey Decimal Classification:

    005.8 Data security

  • Funders:

    University of Technology Sydney; CSIRO

Citation

Tan, Z., Jamdagni, A., Nanda, P., He, X., & Liu, R. P. (2012). Evaluation on multivariate correlation analysis based denial-of-service attack detection system. In SecurIT '12 Proceedings of the First International Conference on Security of Internet of Things, 160-164. https://doi.org/10.1145/2490428.2490450

Authors

Keywords

multivariate correlations, network traffic characterization, denial-of-service attack, euclidean distance

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