Anomaly Detection System for Network Traffic using Data Mining: Machine Learning Perspective - Couverture souple

Sharma, Ruby ; Chaurasia, Sandeep

9786203305234: Anomaly Detection System for Network Traffic using Data Mining: Machine Learning Perspective

Couverture souple

ISBN 10 : 6203305235 ISBN 13 : 9786203305234

Editeur : LAP LAMBERT Academic Publishing, 2021

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Anomaly detection using Density Maximization Fuzzy C-means Algorithm: The rationale for the anomaly detection system using density maximization approach to the fuzzy c-means clustering algorithm. The workflow of a proposed anomaly detection system with density maximization FCM algorithm. The framework of ensemble classifier-based anomaly detection - this approach of anomalous detection is based on the integration of multiple classifiers so that the weakness of one classifier can be compensated by the other classifier. The workflow of the proposed intrusion detection framework based on an ensemble classifier.

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�diteur: LAP LAMBERT Academic Publishing
Date d'�dition: 2021
Langue: anglais
ISBN 10: 6203305235
ISBN 13: 9786203305234
Reliure: Broch�
Nombre de pages: 144
Coordonn�es du fabricant: non disponible
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Anomaly Detection System for Network Traffic using Data Mining

Ruby Sharma

Edit� par LAP LAMBERT Academic Publishing Jan 2021, 2021

ISBN 10 : 6203305235 ISBN 13 : 9786203305234

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Anomaly detection using Density Maximization Fuzzy C-means Algorithm: The rationale for the anomaly detection system using density maximization approach to the fuzzy c-means clustering algorithm. The workflow of a proposed anomaly detection system with density maximization FCM algorithm. The framework of ensemble classifier-based anomaly detection - this approach of anomalous detection is based on the integration of multiple classifiers so that the weakness of one classifier can be compensated by the other classifier. The workflow of the proposed intrusion detection framework based on an ensemble classifier. 144 pp. Englisch. N� de r�f. du vendeur 9786203305234

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Anomaly Detection System for Network Traffic using Data Mining

Ruby Sharma|Sandeep Chaurasia

Edit� par LAP LAMBERT Academic Publishing, 2021

ISBN 10 : 6203305235 ISBN 13 : 9786203305234

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Kartoniert / Broschiert. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Sharma RubyDr. Ruby Sharma is working as an Associate Professor in the Institute of Information Technology & Management, Guru Gobind Singh Indraprastha University, New DelhiDr. Sandeep Chaurasia is working as a Professor in the Depar. N� de r�f. du vendeur 452579674

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Anomaly Detection System for Network Traffic using Data Mining : Machine Learning Perspective

Ruby Sharma

Edit� par LAP LAMBERT Academic Publishing, 2021

ISBN 10 : 6203305235 ISBN 13 : 9786203305234

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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Anomaly detection using Density Maximization Fuzzy C-means Algorithm: The rationale for the anomaly detection system using density maximization approach to the fuzzy c-means clustering algorithm. The workflow of a proposed anomaly detection system with density maximization FCM algorithm. The framework of ensemble classifier-based anomaly detection - this approach of anomalous detection is based on the integration of multiple classifiers so that the weakness of one classifier can be compensated by the other classifier. The workflow of the proposed intrusion detection framework based on an ensemble classifier. N� de r�f. du vendeur 9786203305234

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Anomaly Detection System for Network Traffic using Data Mining

Ruby Sharma

Edit� par LAP LAMBERT Academic Publishing Jan 2021, 2021

ISBN 10 : 6203305235 ISBN 13 : 9786203305234

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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Anomaly detection using Density Maximization Fuzzy C-means Algorithm: The rationale for the anomaly detection system using density maximization approach to the fuzzy c-means clustering algorithm. The workflow of a proposed anomaly detection system with density maximization FCM algorithm. The framework of ensemble classifier-based anomaly detection - this approach of anomalous detection is based on the integration of multiple classifiers so that the weakness of one classifier can be compensated by the other classifier. The workflow of the proposed intrusion detection framework based on an ensemble classifier.VDM Verlag, Dudweiler Landstra�e 99, 66123 Saarbr�cken 144 pp. Englisch. N� de r�f. du vendeur 9786203305234

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Anomaly Detection System for Network Traffic using Data Mining | Machine Learning Perspective

Ruby Sharma (u. a.)

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ISBN 10 : 6203305235 ISBN 13 : 9786203305234

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Anomaly Detection System for Network Traffic using Data Mining: Machine Learning Perspective - Couverture souple

Sharma, Ruby; Chaurasia, Sandeep

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