Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2018
ISBN 10: 6139896622 ISBN 13: 9786139896622
Da: Revaluation Books, Exeter, Regno Unito
EUR 98,16
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 92 pages. 8.66x5.91x0.21 inches. In Stock.
Lingua: Inglese
Editore: LAP Lambert Academic Publishing, 2018
ISBN 10: 6139896622 ISBN 13: 9786139896622
Da: preigu, Osnabrück, Germania
EUR 47,85
Quantità: 5 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Intrusion Detection System Using SPARK'S Machine Learning Library | Secure your network | Pradeep Laxkar (u. a.) | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9786139896622 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2018
ISBN 10: 6139896622 ISBN 13: 9786139896622
Da: moluna, Greven, Germania
EUR 46,15
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Laxkar PradeepDr Pradeep Laxkar is working as associate professor and Head of Department of Computer Engineering at ITM Universe Vadodara. He is having 13 years of academic experience and his area of interest is information security.
Lingua: Inglese
Editore: LAP Lambert Academic Publishing, 2018
ISBN 10: 6139896622 ISBN 13: 9786139896622
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 55,56
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Now a day's computer network security problems play a pivotal role. The network is vulnerable towards attacks like DOS, U2R, R2L etc. These attacks take advantage of a network vulnerability to gain illegal access to important information or sometimes create a flood to prevent genuine users from accessing it. Network attackers use massive volume of network traffic in short span of time to create a victim host unavailable whereby a fast and efficient network intrusion detection is a very challenging issue. The size of network traffic has turned into increasingly big and complex and the proposed intrusion detection system should be able to process huge size of network data in order to detect intrusion in the network as early as possible. This book entails the implementation of network intrusion detection system using association rule generation and quadric classification using machine learning library of spark.