20092009 ICCAS-SICERequires access

Intrusion detection system combining misuse detection and anomaly detection using Genetic Network Programming

Yunlu Gong, Shingo Mabu, Ci Chen, Yifei Wang, Kotaro Hirasawa

Open publisher page 28 citations

Abstract

In this paper, a class association rule mining approach based on Genetic Network Programming(GNP) for detecting network intrusion combining misuse detection and anomaly detection is proposed. The proposed approach is an extension of the intrusion detection approach using GNP, so it can detect and distinguish normal, known intrusion and unknown intrusion. The simulation result shows that the detection rate is improved compared with traditional intrusion detection approach, and normal, known intrusion and unknown intrusion are distinguished with high accuracy.

About this research paper

What this paper is about

In this paper, a class association rule mining approach based on Genetic Network Programming(GNP) for detecting network intrusion combining misuse detection and anomaly detection is proposed. The proposed approach is an extension of the intrusion detection approach using GNP, so it can detect and distinguish normal, known intrusion and unknown intrusion. The simulation result shows that the detection rate is improved compared with traditional intrusion detection approach, and normal, known intrusion and unknown intrusion are distinguished with high accuracy.

Why it matters

OpenAlex reports 28 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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Available abstract

In this paper, a class association rule mining approach based on Genetic Network Programming(GNP) for detecting network intrusion combining misuse detection and anomaly detection is proposed. The proposed approach is an extension of the intrusion detection approach using GNP, so it can detect and distinguish normal, known intrusion and unknown intrusion. The simulation result shows that the detection rate is improved compared with traditional intrusion detection approach, and normal, known intrusion and unknown intrusion are distinguished with high accuracy.

Key concepts: Intrusion detection system, Anomaly-based intrusion detection system, Misuse detection, Computer science, Anomaly detection, Data mining, Intrusion, Genetic programming

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