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An Evaluation of Intrusion Detection System on Jubatus

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Progress in Systems Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 366))

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Abstract

The network intrusion is becoming a big threat for a lot of companies, organization and so on. Recent intrusions are becoming more clever and difficult to detect. Many of today’s intrusion detection systems are based on signature-based. They have good performance for known attacks, but theoretically they are not able to detect unknown attacks. On the other hand, an anomaly detection system can detect unknown attacks and is getting focus recently. In this paper, we study the effectiveness and the performance experiments of one of the major anomaly detection scales, LOF, on distributed online machine learning framework, Jubatus.

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References

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Author information

Authors and Affiliations

  1. Department of Information and Communication Systems Engineering, Okinawa National College of Technology, Okinawa, Japan

    Tadashi Ogino

Authors
  1. Tadashi Ogino
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Correspondence to Tadashi Ogino .

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Editors and Affiliations

  1. University of Nevada at Las Vegas, Las Vegas, Nevada, USA

    Henry Selvaraj

  2. Department of Electrical Engineering, Idaho State University, Pocatello, Idaho, USA

    Dawid Zydek

  3. University of Nevada at Las Vegas, Las Vegas, Nevada, USA

    Grzegorz Chmaj

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© 2015 Springer International Publishing Switzerland

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Ogino, T. (2015). An Evaluation of Intrusion Detection System on Jubatus. In: Selvaraj, H., Zydek, D., Chmaj, G. (eds) Progress in Systems Engineering. Advances in Intelligent Systems and Computing, vol 366. Springer, Cham. https://doi.org/10.1007/978-3-319-08422-0_53

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  • DOI: https://doi.org/10.1007/978-3-319-08422-0_53

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08421-3

  • Online ISBN: 978-3-319-08422-0

  • eBook Packages: EngineeringEngineering (R0)

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