Design and Implementation of a Decision Tree Algorithm-Based Network Intrusion Detection System

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Mrs U.Prathibha; A.M.Arun Prakesh; E.Avinash

Design and Implementation of a Decision Tree Algorithm-Based Network Intrusion Detection System

Authors: Mrs U.Prathibha, A.M.Arun Prakesh, E.Avinash

Unique Paper ID: 176325
Volume: 11
Issue: 11
PageNo: 5174-5177

Keywords: Network Intrusion Detection Decision Tree Machine Learning Security Intrusion Detection Systems Classification Attack Detection

Abstract:
The rapid evolution of networked systems has led to an increase in sophisticated cyber-attacks, making it critical to detect and prevent unauthorized access and threats in real time. Intrusion Detection Systems (IDS) are crucial components in network security that analyze traffic and identify any unusual or potentially malicious behavior. Among various IDS approaches, machine learning-based methods, specifically Decision Tree (DT) algorithms, have gained attention due to their simplicity, interpretability, and good classification performance. This paper proposes the use of a Decision Tree-based model for a Network Intrusion Detection System. We leverage the Decision Tree’s ability to handle both categorical and numerical data, its transparency in decision-making, and its capacity to build easily interpretable models. This system aims to detect a variety of attacks, such as Denial of Service (DoS), Probe, and User-to-Root (U2R), while minimizing false positives.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 11
PageNo: 5174-5177

Design and Implementation of a Decision Tree Algorithm-Based Network Intrusion Detection System

Available:https://ijirt.org/article?manuscript=176325

23 Apr, 2025

MICRO ORGANISM IMAGE CLASSIFICATION USING DEEP LEARNING

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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