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Integrating Intrusion Detection System and Data Mining

Sattarova Feruza Yusufovna

Open publisher page 22 citations

Abstract

This paper presents the application of data mining approaches for an intrusion detection system. Intrusion detection is the act of detecting actions that attempt to compromise the confidentiality, integrity or availability of the resource of a computer system. In this paper, an IDS model is presented as well as its limitation in determining security violations. Furthermore, this paper focuses on several data mining techniques that can aid in the process of intrusion detection.

About this research paper

What this paper is about

This paper presents the application of data mining approaches for an intrusion detection system. Intrusion detection is the act of detecting actions that attempt to compromise the confidentiality, integrity or availability of the resource of a computer system. In this paper, an IDS model is presented as well as its limitation in determining security violations. Furthermore, this paper focuses on several data mining techniques that can aid in the process of intrusion detection.

Why it matters

OpenAlex reports 22 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

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Method / approach

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Main findings

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Available abstract

This paper presents the application of data mining approaches for an intrusion detection system. Intrusion detection is the act of detecting actions that attempt to compromise the confidentiality, integrity or availability of the resource of a computer system. In this paper, an IDS model is presented as well as its limitation in determining security violations. Furthermore, this paper focuses on several data mining techniques that can aid in the process of intrusion detection.

Key concepts: Intrusion detection system, Anomaly-based intrusion detection system, Computer science, Confidentiality, Compromise, Process (computing), Intrusion, Data mining

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