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Evaluation of Model Using J-48 and Other Classifier on Kddcup99 Through Performance Metrics

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Advanced Informatics for Computing Research (ICAICR 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1075))

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Abstract

Intrusion detection system (IDS) is one of the complete solution against harmful attacks, as well as the attackers always keep changeable their tools and techniques. However, implementing an approved intrusion detection system is also a challenging task. In this paper, we have taken the dataset of KDDCUP99. KDD cup99 is the most widely used data set for the evaluation of the system in anomaly based detection. This paper we have used twelve attributes from the KDD 99 dataset and weka tool for simulation. In this paper J-48 with other classifier shows the better results in terms of precision and recall metrics. It achieves to compute several performance metrics are available for the measurement in order to evaluate the selected classifiers.

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Authors and Affiliations

  1. Institute of Technology and Management Group of Institutions, Gwalior, India

    Saby Singhal & Pradeep Yadav

Authors
  1. Saby Singhal
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  2. Pradeep Yadav
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Corresponding author

Correspondence to Saby Singhal .

Editor information

Editors and Affiliations

  1. Papua New Guinea University of Technology, Lae, Papua New Guinea

    Ashish Kumar Luhach

  2. Computer Science Department, Namibia University of Science and Technology, Windhoek, Namibia

    Dharm Singh Jat

  3. Universiti Malaysia Pahang, Pekan, Pahang, Malaysia

    Kamarul Bin Ghazali Hawari

  4. School of Computing, University of Eastern Finland, Kuopio, Finland

    Xiao-Zhi Gao

  5. Department of Mathematics and Computing Science, Saint Mary's University, Halifax, Canada

    Pawan Lingras

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Singhal, S., Yadav, P. (2019). Evaluation of Model Using J-48 and Other Classifier on Kddcup99 Through Performance Metrics. In: Luhach, A., Jat, D., Hawari, K., Gao, XZ., Lingras, P. (eds) Advanced Informatics for Computing Research. ICAICR 2019. Communications in Computer and Information Science, vol 1075. Springer, Singapore. https://doi.org/10.1007/978-981-15-0108-1_2

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  • DOI: https://doi.org/10.1007/978-981-15-0108-1_2

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-0107-4

  • Online ISBN: 978-981-15-0108-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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