ManageChatDiscover
205079

A New Intrusion Detection Strategy Based on Combined Feature Selection Methodology and Machine Learning Technique.

Article

Last updated: 04 Jan 2025

OverviewSimilar Items

Subjects

-

Tags

Electronics and Communications Engineering

Abstract

Intrusion detection system is a significant security mechanism that monitors network traffic to assist prevents unwanted access to network resources. Effective intrusion detection is an important issue for defending networks against potential intrusions. In this paper, a new intrusion detection strategy is proposed. The recommended intrusion detection strategy is divided into three steps: (i) Preparing step, (ii) Feature selection step, and (iii) Classification step. Preparing step gathers and analyzes network traffic in readiness for training and testing. Feature selection step aims to choose the significant features for detecting intrusion attacks form preparing step. It comprises of two successive feature selection modules, which are; quick selection module and precise selection module.  Precise selection module deploys genetic algorithm as a wrapper method, whereas quick selection module relies on filter. Based on the most effective features identified by feature selection step, the classification step seeks to detect intrusion attacks with the least amount of time penalty. It contains two phases: prioritized naive bayes phase and distance encouragement phase, which avoids the problems of naive bayes classifiers. The presented intrusion detection strategy beats other previous approaches using the NSL-KDD dataset, according to the experimental tests.  Intrusion detection strategy provides the highest accuracy, precision, recall and F1-measure with values equal to 97.6%, 98.24%, 98.14%, and 98.11% respectively with minimum time penalty.

DOI

10.21608/bfemu.2021.205079

Keywords

Intrusion Detection System, Feature Selection, Machine Learning, Genetic Algorithm

Authors

First Name

Shereen

Last Name

Ali

MiddleName

Hassan

Affiliation

Assistant Professor of Communications & Electronics Engineering Department, Delta Higher Institute for Engineering & Technology, Mansoura, Egypt

Email

engshereen2011@gmail.com

City

Mansoura

Orcid

-

Volume

46

Article Issue

4

Related Issue

28611

Issue Date

2021-12-01

Receive Date

2021-10-02

Publish Date

2021-11-16

Page Start

27

Page End

35

Print ISSN

1110-0923

Online ISSN

2735-4202

Article File

BFEMU_Volume 46_Issue 4_Pages 27-35.pdf

PDF . 900.7kB

Link

https://bfemu.journals.ekb.eg/article_205079.html

Detail API

https://bfemu.journals.ekb.eg/service?article_code=205079

Order

18

Type

Research Studies

Type Code

1,205

Publication Type

Journal

Publication Title

MEJ. Mansoura Engineering Journal

Publication Link

https://bfemu.journals.ekb.eg/

MainTitle

A New Intrusion Detection Strategy Based on Combined Feature Selection Methodology and Machine Learning Technique.

Details

Type

Article

Created At

22 Jan 2023