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2015•Unpublished venueRequires access

Data Mining Techniques for Intrusion Detection

Prashant D. Joshi, M. Tech, Kamlesh Padaliya

Open publisher page 11 citations

Abstract

Intrusion detection can be defined as an act of detecting actions that attempt to compromise the confidentiality, integrity or availability of any network resource. In this paper we discuss the different data mining techniques for intrusion detection. We review some of the existing ensemble methods used in intrusion detection. We also propose an ensemble method for the problem of intrusion detection.

About this research paper

What this paper is about

Intrusion detection can be defined as an act of detecting actions that attempt to compromise the confidentiality, integrity or availability of any network resource. In this paper we discuss the different data mining techniques for intrusion detection. We review some of the existing ensemble methods used in intrusion detection. We also propose an ensemble method for the problem of intrusion detection.

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OpenAlex reports 11 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Method / approach

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Available abstract

Intrusion detection can be defined as an act of detecting actions that attempt to compromise the confidentiality, integrity or availability of any network resource. In this paper we discuss the different data mining techniques for intrusion detection. We review some of the existing ensemble methods used in intrusion detection. We also propose an ensemble method for the problem of intrusion detection.

Key concepts: Intrusion detection system, Anomaly-based intrusion detection system, Computer science, Data mining, Confidentiality, Intrusion, Computer security, Geology

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