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Network intrusion detection is one of the central systems used in cyber security to prevent the intrusions in the organisation's networks. Tackling the attempts to compromise the confidentiality, integrity and availability of computer networks' security mechanisms in a big data environment is the most challenging task due to the volume and variety of big data. This study presented to tackle the challenges in network Intrusion Detection Systems (IDS) and demonstrate intelligent algorithms' development to detect the intrusions in big network data. The problem is the practical selection of the features from the network dataset as it dramatically impacts the intrusion detection accuracy. Hence, an efficient feature selection approach must be introduced to achieve higher accuracy with a reduced number of features.
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- VerlagLAP LAMBERT Academic Publishing
- Erscheinungsdatum2023
- ISBN 10 6206158853
- ISBN 13 9786206158851
- EinbandTapa blanda
- SpracheEnglisch
- Anzahl der Seiten236
- Kontakt zum HerstellerNicht verfügbar
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Intrusion Detection
Verlag:
LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206158853
ISBN 13: 9786206158851
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ramasamy GunavathiDr. R. Gunavathi is working as Associate Professor, CHRIST University. Her current research interest is in Mobile Ad Hoc Networks, Vehicular Ad hoc Networks, Data Analytics and Bigdata Analytics. She has produced 3. Bestandsnummer des Verkäufers 872703939
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Intrusion Detection
Verlag:
LAP LAMBERT Academic Publishing Apr 2023, 2023
ISBN 10: 6206158853
ISBN 13: 9786206158851
Neu
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Taschenbuch. Zustand: Neu. Neuware -Network intrusion detection is one of the central systems used in cyber security to prevent the intrusions in the organisation's networks. Tackling the attempts to compromise the confidentiality, integrity and availability of computer networks' security mechanisms in a big data environment is the most challenging task due to the volume and variety of big data. This study presented to tackle the challenges in network Intrusion Detection Systems (IDS) and demonstrate intelligent algorithms' development to detect the intrusions in big network data. The problem is the practical selection of the features from the network dataset as it dramatically impacts the intrusion detection accuracy. Hence, an efficient feature selection approach must be introduced to achieve higher accuracy with a reduced number of features.Books on Demand GmbH, Überseering 33, 22297 Hamburg 236 pp. Englisch. Bestandsnummer des Verkäufers 9786206158851
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Intrusion Detection
Verlag:
LAP LAMBERT Academic Publishing Apr 2023, 2023
ISBN 10: 6206158853
ISBN 13: 9786206158851
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Network intrusion detection is one of the central systems used in cyber security to prevent the intrusions in the organisation's networks. Tackling the attempts to compromise the confidentiality, integrity and availability of computer networks' security mechanisms in a big data environment is the most challenging task due to the volume and variety of big data. This study presented to tackle the challenges in network Intrusion Detection Systems (IDS) and demonstrate intelligent algorithms' development to detect the intrusions in big network data. The problem is the practical selection of the features from the network dataset as it dramatically impacts the intrusion detection accuracy. Hence, an efficient feature selection approach must be introduced to achieve higher accuracy with a reduced number of features. 236 pp. Englisch. Bestandsnummer des Verkäufers 9786206158851
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Intrusion Detection : Map Reduce Based Deep Learning In Big Data Environment
Verlag:
LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206158853
ISBN 13: 9786206158851
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Network intrusion detection is one of the central systems used in cyber security to prevent the intrusions in the organisation's networks. Tackling the attempts to compromise the confidentiality, integrity and availability of computer networks' security mechanisms in a big data environment is the most challenging task due to the volume and variety of big data. This study presented to tackle the challenges in network Intrusion Detection Systems (IDS) and demonstrate intelligent algorithms' development to detect the intrusions in big network data. The problem is the practical selection of the features from the network dataset as it dramatically impacts the intrusion detection accuracy. Hence, an efficient feature selection approach must be introduced to achieve higher accuracy with a reduced number of features. Bestandsnummer des Verkäufers 9786206158851
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Intrusion Detection: Map Reduce Based Deep Learning In Big Data Environment
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ISBN 10: 6206158853
ISBN 13: 9786206158851
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Intrusion Detection: Map Reduce Based Deep Learning In Big Data Environment
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ISBN 10: 6206158853
ISBN 13: 9786206158851
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Intrusion Detection: Map Reduce Based Deep Learning In Big Data Environment
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LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206158853
ISBN 13: 9786206158851
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Intrusion Detection: Map Reduce Based Deep Learning In Big Data Environment
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ISBN 13: 9786206158851
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