Network Intrusion Detection System using Machine Learning Techniques: A Quick Reference - Couverture souple

Sindhu, Siva S. Sivatha; Geetha, S.; Selvakumar, S.

 
9783659410352: Network Intrusion Detection System using Machine Learning Techniques: A Quick Reference
Couverture souple
ISBN 10 : 3659410357 ISBN 13 : 9783659410352
Editeur : LAP LAMBERT Academic Publishing, 2013

Synopsis

This book presents the need for intrusion detection system as it has become an essential concern with the growing use of internet and increased network attacks such as virus, Trojan horse, worms and creative hackers. In addition, the basic details about the historic origin of IDS, the types of IDS, their deployment schemes and general architecture are considered. IDS using various machine learning techniques like fuzzy logic, genetic algorithm, neural network, decision tree etc are discussed and their pros and cons are discussed. Another potential approach is ensemble learning, which have been successfully applied to IDS for differentiating normal and anomalous types. In this book, various ensemble approaches like neuro-genetic, neuro-fuzzy, neurotree etc are explained. The implementation of these IDS depends again on the requirement of the security administrator. The IDS discussed in this book are adaptive to new environments by updating the audit data with recent attacks. If new attacks are identified these approaches can store the attack patterns in log generator for detecting future attacks.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

This book presents the need for intrusion detection system as it has become an essential concern with the growing use of internet and increased network attacks such as virus, Trojan horse, worms and creative hackers. In addition, the basic details about the historic origin of IDS, the types of IDS, their deployment schemes and general architecture are considered. IDS using various machine learning techniques like fuzzy logic, genetic algorithm, neural network, decision tree etc are discussed and their pros and cons are discussed. Another potential approach is ensemble learning, which have been successfully applied to IDS for differentiating normal and anomalous types. In this book, various ensemble approaches like neuro-genetic, neuro-fuzzy, neurotree etc are explained. The implementation of these IDS depends again on the requirement of the security administrator. The IDS discussed in this book are adaptive to new environments by updating the audit data with recent attacks. If new attacks are identified these approaches can store the attack patterns in log generator for detecting future attacks.

Biographie de l'auteur

Dr.Siva S.Sivatha Sindhu received her PhD in Information Security from Anna University,Chennai. She is a member of IEEE and CSI. She has published more than 40 research papers in reputed journals including Elsevier, Springer etc. Her areas of interest are Intrusion Detection System, Machine Laearning Techniques, Network Security etc.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2013
Langue
anglais
ISBN 10 
3659410357
ISBN 13 
9783659410352
Reliure
Broché
Nombre de pages
80
Coordonnées du fabricant
non disponible
Personne responsable
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