data mining approach intrusion von palaniswamy amudha (8 Ergebnisse)

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Taschenbuch. Zustand: Neu. Data Mining Approach for Intrusion Detection System | Amudha Palaniswamy | Taschenbuch | 88 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786139952731 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -There is a tremendous growth in the field of information technology due to which, network security is also facing significant challenge.The traditional Intrusion Detection System (IDS) is unable to handle the recent attacks and malware's. Hence, IDS which is an indispensable component of the network needs to be protected. Data mining based network intrusion detection is widely used to identify how and where the intrusions occur. Reducing the number of features by selecting the important features is critical to improve the accuracy and speed of classification algorithms. In order to improve the accuracy of an individual classifier, the classifiers are combined which is the prevalent approach. This book covers the concept of selecting the significant features using bio-inspired approach and develop a hybrid classifier model for IDS in terms of high accuracy and detection rates. 88 pp. Englisch.

Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Palaniswamy AmudhaP.Amudha graduated her B.E in CSE, M.Tech in IT & obtained her Ph.D. in Information and Communication Engineering from Anna University. Currently she is working as Associate Professor in the Dept of CSE, Avinashili.

Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -There is a tremendous growth in the field of information technology due to which, network security is also facing significant challenge.The traditional Intrusion Detection System (IDS) is unable to handle the recent attacks and malware's. Hence, IDS which is an indispensable component of the network needs to be protected. Data mining based network intrusion detection is widely used to identify how and where the intrusions occur. Reducing the number of features by selecting the important features is critical to improve the accuracy and speed of classification algorithms. In order to improve the accuracy of an individual classifier, the classifiers are combined which is the prevalent approach. This book covers the concept of selecting the significant features using bio-inspired approach and develop a hybrid classifier model for IDS in terms of high accuracy and detection rates.Books on Demand GmbH, Überseering 33, 22297 Hamburg 88 pp. Englisch.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - There is a tremendous growth in the field of information technology due to which, network security is also facing significant challenge.The traditional Intrusion Detection System (IDS) is unable to handle the recent attacks and malware's. Hence, IDS which is an indispensable component of the network needs to be protected. Data mining based network intrusion detection is widely used to identify how and where the intrusions occur. Reducing the number of features by selecting the important features is critical to improve the accuracy and speed of classification algorithms. In order to improve the accuracy of an individual classifier, the classifiers are combined which is the prevalent approach. This book covers the concept of selecting the significant features using bio-inspired approach and develop a hybrid classifier model for IDS in terms of high accuracy and detection rates.

Zustand: New. Print on Demand.

Zustand: New. PRINT ON DEMAND.