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Human Gait Recognition Using Gait Flow Image and Extension Neural Network Read chapter Read first chapter

2016 | OriginalPaper | Chapter

A Minimal Subset of Features Using Correlation Feature Selection Model for Intrusion Detection System

Authors : Shilpa Bahl, Sudhir Kumar Sharma

Published in: Proceedings of the Second International Conference on Computer and Communication Technologies

Publisher: Springer India

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Abstract

The intrusion detection system (IDS) research field has grown tremendously in the past decade. Current IDS uses all data features to detect intrusions. Some of the features may be irrelevant and redundant to the detection process. The purpose of this study is to identify a minimal subset of relevant features to design effective intrusion detection system. A proposed minimal subset of features is built by selecting common features from six search methods with correlation feature selection method. The paper presents empirical comparison between 7 reduced subsets and the given complete set of features. The simulation results have shown slightly better performance using only 12 proposed features compared to others.

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previous chapter Secured Authentication and Signature Routing Protocol for WMN (SASR)
next chapter Analysis of Single-Layered Multiple Aperture Shield for Better Shield Effectiveness
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Metadata
Title
A Minimal Subset of Features Using Correlation Feature Selection Model for Intrusion Detection System
Authors
Shilpa Bahl
Sudhir Kumar Sharma
Copyright Year
2016
Publisher
Springer India
Book
Proceedings of the Second International Conference on Computer and Communication Technologies

Print ISBN: 978-81-322-2522-5

Electronic ISBN: 978-81-322-2523-2

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-81-322-2523-2_32