Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2016
ISBN 10: 365997921X ISBN 13: 9783659979217
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Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2016
ISBN 10: 365997921X ISBN 13: 9783659979217
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Hybrid Intrusion Detection | Clustering-Outlier and Incremental SVM | Roshan Chitrakar (u. a.) | Taschenbuch | 140 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659979217 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2016
ISBN 10: 365997921X ISBN 13: 9783659979217
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Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing Nov 2016, 2016
ISBN 10: 365997921X ISBN 13: 9783659979217
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Newer intrusions are coming out every day with the all-way growth of the Internet. In this context, this book proposes a hybrid approach of intrusion detection along with architecture. The proposed architecture is flexible enough to carry intrusion detection tasks either by using a single module or by using multiple modules. Two modules - (1) Clustering-Outlier detection followed by SVM classification and (2) Incremental SVM with Half-partition method, are proposed in the book. Firstly, this work develops the 'Clustering-Outlier Detection' algorithm that combines k-Medoids clustering and Outlier analysis. Secondly, this book introduces the Half-partition strategy and also designs 'Candidate Support Vector Selection' algorithm for incremental SVM. This book is intended for the people who are working in the field of Intrusion Detection and Data Mining. Researchers and Scholars who are interested in k-Means and k-Medoids clustering and SVM classification in particular, will find this book useful. Students who want to pursue their research work in the fields of Information Security and Data Mining may also consider this as a good reference. 140 pp. Englisch.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2016
ISBN 10: 365997921X ISBN 13: 9783659979217
Da: moluna, Greven, Germania
EUR 46,18
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Chitrakar RoshanRoshan Chitrakar, born in 1967, is a Ph.D. in Information Security of Wuhan University, China. His areas of interests are Data Mining, Programming Languages, Software Engineering, Databases etc. Starting IT career in .
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing Nov 2016, 2016
ISBN 10: 365997921X ISBN 13: 9783659979217
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 55,90
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Newer intrusions are coming out every day with the all-way growth of the Internet. In this context, this book proposes a hybrid approach of intrusion detection along with architecture. The proposed architecture is flexible enough to carry intrusion detection tasks either by using a single module or by using multiple modules. Two modules - (1) Clustering-Outlier detection followed by SVM classification and (2) Incremental SVM with Half-partition method, are proposed in the book. Firstly, this work develops the 'Clustering-Outlier Detection' algorithm that combines k-Medoids clustering and Outlier analysis. Secondly, this book introduces the Half-partition strategy and also designs 'Candidate Support Vector Selection' algorithm for incremental SVM. This book is intended for the people who are working in the field of Intrusion Detection and Data Mining. Researchers and Scholars who are interested in k-Means and k-Medoids clustering and SVM classification in particular, will find this book useful. Students who want to pursue their research work in the fields of Information Security and Data Mining may also consider this as a good reference.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 140 pp. Englisch.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2016
ISBN 10: 365997921X ISBN 13: 9783659979217
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 56,57
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Newer intrusions are coming out every day with the all-way growth of the Internet. In this context, this book proposes a hybrid approach of intrusion detection along with architecture. The proposed architecture is flexible enough to carry intrusion detection tasks either by using a single module or by using multiple modules. Two modules - (1) Clustering-Outlier detection followed by SVM classification and (2) Incremental SVM with Half-partition method, are proposed in the book. Firstly, this work develops the 'Clustering-Outlier Detection' algorithm that combines k-Medoids clustering and Outlier analysis. Secondly, this book introduces the Half-partition strategy and also designs 'Candidate Support Vector Selection' algorithm for incremental SVM. This book is intended for the people who are working in the field of Intrusion Detection and Data Mining. Researchers and Scholars who are interested in k-Means and k-Medoids clustering and SVM classification in particular, will find this book useful. Students who want to pursue their research work in the fields of Information Security and Data Mining may also consider this as a good reference.
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Da: Biblios, Frankfurt am main, HESSE, Germania
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Da: moluna, Greven, Germania
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dan Dobrota is a Professor at Lucian Blaga University of Sibiu, Romania. He obtained his undergraduate degree in Machine Building Technology (1994) from University of Craiova, Romania. He received his Ph.D. in Technology of Materials field from th.
Da: preigu, Osnabrück, Germania
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Aggiungi al carrelloBuch. Condizione: Neu. Computational Social Science | Proceedings of the 2nd International Conference on New Computational Social Science (ICNCSS 2021), October 15-17, 2021, Suzhou, Jiangsu, China | Dan Dobrota (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2022 | Routledge | EAN 9781032303765 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 290,44
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Aggiungi al carrelloBuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - A selection of papers focusing on the following five aspects: Big data acquisition and analysis, Integration of qualitative research and quantitative research, Sociological Internet experiment research, Application of ABM simulation method in Sociology Research, Research and development of new social computing tools.