9783659642425 - data mining, knowledge discovery in databases:: hybrid anomaly detection approach von gadal, saad; mokhtar, rania (6 Ergebnisse)

- Softcover
Anbieter: Revaluation Books, Exeter, Vereinigtes KönigreichRevaluation Books
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 91,88
EUR 11,61 VersandVersand von Vereinigtes Königreich nach USAAnzahl: 1 verfügbar
Paperback. Zustand: Brand New. 88 pages. 8.66x5.91x0.20 inches. In Stock.

- Softcover
Anbieter: preigu, Osnabrück, Deutschlandpreigu
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 44,00
EUR 70,00 VersandVersand von Deutschland nach USAAnzahl: 5 verfügbar
Taschenbuch. Zustand: Neu. Data Mining, Knowledge Discovery in Databases: | Hybrid Anomaly Detection Approach | Saad Gadal (u. a.) | Taschenbuch | 88 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783659642425 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail…[at]preigu[dot]de | Anbieter: preigu.

- Softcover
- Print-on-Demand
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, DeutschlandBuchWeltWeit Ludwig Meier e.K.
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 49,90
EUR 23,00 VersandVersand von Deutschland nach USAAnzahl: 2 verfügbar
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This Book discusses hybrid machine learning technique for network intrusion detection based on combination of K-means clustering and Sequential Minimal Optimization classification. Intrusion is one of the main threats to the internet.… Hence security issues had been big problem, so that various techniques and approaches have been presented to address the limitations of intrusion detection system such as low accuracy, high false alarm rate, and time consuming. The aim of this book is to introduce research chapters for hybrid approach that able to reduce the rate of false positive alarm, to improve the detection rate and detect zero-day attackers and to get high accuracy for classify intrusion. The NSL-KDD dataset has been used to evaluate the proposed technique. In order to improve classification performance, some steps have been taken on the dataset like feature selection. The classification has been performed by using (Sequential Minimal Optimization SMO + K-mean clustering). After training and testing the hybrid machine learning technique, the results have shown that the proposed technique has achieved a positive detection rate, reduce the false alarm rate and get high accuracy. 88 pp. Englisch.

- Softcover
- Print-on-Demand
Anbieter: moluna, Greven, Deutschlandmoluna
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 41,71
EUR 48,99 VersandVersand von Deutschland nach USAAnzahl: Mehr als 20 verfügbar
Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Gadal SaadSaad Galal received the B.Sc. degree and the M.Sc in Computer Engineering from the Sudan University of Science and Technology (SUST), Khartoum, Sudan, in the field of Computer Engineering - Rani…a Abdelhameed received PhD de.

- Softcover
- Print-on-Demand
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschlandbuchversandmimpf2000
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 49,90
EUR 60,00 VersandVersand von Deutschland nach USAAnzahl: 1 verfügbar
Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This Book discusses hybrid machine learning technique for network intrusion detection based on combination of K-means clustering and Sequential Minimal Optimization classification. Intrusion is one of the main threats to the internet. Hen…ce security issues had been big problem, so that various techniques and approaches have been presented to address the limitations of intrusion detection system such as low accuracy, high false alarm rate, and time consuming. The aim of this book is to introduce research chapters for hybrid approach that able to reduce the rate of false positive alarm, to improve the detection rate and detect zero-day attackers and to get high accuracy for classify intrusion. The NSL-KDD dataset has been used to evaluate the proposed technique. In order to improve classification performance, some steps have been taken on the dataset like feature selection. The classification has been performed by using (Sequential Minimal Optimization SMO + K-mean clustering). After training and testing the hybrid machine learning technique, the results have shown that the proposed technique has achieved a positive detection rate, reduce the false alarm rate and get high accuracy.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 88 pp. Englisch.

- Softcover
- Print-on-Demand
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 50,50
EUR 60,75 VersandVersand von Deutschland nach USAAnzahl: 1 verfügbar
Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This Book discusses hybrid machine learning technique for network intrusion detection based on combination of K-means clustering and Sequential Minimal Optimization classification. Intrusion is one of the main threats to the internet. Henc…e security issues had been big problem, so that various techniques and approaches have been presented to address the limitations of intrusion detection system such as low accuracy, high false alarm rate, and time consuming. The aim of this book is to introduce research chapters for hybrid approach that able to reduce the rate of false positive alarm, to improve the detection rate and detect zero-day attackers and to get high accuracy for classify intrusion. The NSL-KDD dataset has been used to evaluate the proposed technique. In order to improve classification performance, some steps have been taken on the dataset like feature selection. The classification has been performed by using (Sequential Minimal Optimization SMO + K-mean clustering). After training and testing the hybrid machine learning technique, the results have shown that the proposed technique has achieved a positive detection rate, reduce the false alarm rate and get high accuracy.