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Kukielka P, Kotulski Z. Analysis of different architectures of neural networks for application in intrusion detection systems. InComputer Science and Information Technology, 2008. IMCSIT 2008. International Multiconference on 2008 Oct 20: 807-811.. IEEE.

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Article

Big Data in Intrusion Detection Systems and Intrusion Prevention Systems

1Department of Engineering Technology, Mississippi Valley State University, Itta Bena, MS, USA


Journal of Computer Networks. 2017, Vol. 4 No. 1, 48-55
DOI: 10.12691/jcn-4-1-5
Copyright © 2017 Science and Education Publishing

Cite this paper:
Lidong Wang. Big Data in Intrusion Detection Systems and Intrusion Prevention Systems. Journal of Computer Networks. 2017; 4(1):48-55. doi: 10.12691/jcn-4-1-5.

Correspondence to: Lidong  Wang, Department of Engineering Technology, Mississippi Valley State University, Itta Bena, MS, USA. Email: lwang22@students.tntech.edu

Abstract

This paper introduces network attacks, intrusion detection systems, intrusion prevention systems, and intrusion detection methods including signature-based detection and anomaly-based detection. Intrusion detection/prevention system (ID/PS) methods are compared. Some data mining and machine learning methods and their applications in intrusion detection are introduced. Big data in intrusion detection systems and Big Data analytics for huge volume of data, heterogeneous features, and real-time stream processing are presented. Challenges of intrusion detection systems and challenges posed by stream processing of big data in the systems are also discussed.

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