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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Chandola, V., Banerjee, A. & Kumar, V.: Anomaly Detection: A Survey. In:ACM Computing Surveys, July.41(3). (2009)
Breunig, M. M., Kriegel, H.-P., Ng, R. T. & Sander, J.,: LOF: Identifying Density-Based Local Outliers. In: Proc. ACM SIGMOD 2000 Int. Conf. On Management of Data (2000)
Jubatus, http://jubat.us/
Lazarevic, A. et al., : A Comparative Study of Anomaly Detection Schemes in Network Intrusion Detection. In: Proceedings of SIAM Conference on Data Mining (2003)
Hawkins, D. M.: Identification of Outliers. London: Chapman and Hall. (1980)
hadoop, http://hadoop.apache.org/
KDDCup1999, https://kdd.ics.uci.edu/databases/kddcup99/kddcup99.html
Aleksandar, L. et al.: A Comparative Study of Anomaly Detection Schemes in Network Intrusion Detection. In: Proceedings of the Third SIAM International Conference on Data Mining. (2003)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
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
Download citation
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)