Sinossi
This work focuses on the development of a new approach based on deep learning to implement an efficient and flexible intrusion detection system using the behavioral approach and mainly intended for critical infrastructures and industrial control systems. Based on the assumption that modeling the normal network behavior of industrial control systems is feasible and reliable, because the operations performed in these systems are quite stationary and repetitive, Convolutional Neural Networks (CNN), a deep learning technique, are used on the NSL-KDD dataset, a reference dataset used for the implementation of intrusion detection systems. The performance of the approach is presented and compared to some previous works. The metrics used include the percentage of correct classification, accuracy and false positives show that the proposed approach improves the performance of previous systems.
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Intrusion Detection System based on deep learning
Da: Books Puddle, New York, NY, U.S.A.
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Intrusion Detection System based on deep learning
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Our Knowledge Publishing Mai 2023, 2023
ISBN 10: 6205985713
ISBN 13: 9786205985717
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This work focuses on the development of a new approach based on deep learning to implement an efficient and flexible intrusion detection system using the behavioral approach and mainly intended for critical infrastructures and industrial control systems. Based on the assumption that modeling the normal network behavior of industrial control systems is feasible and reliable, because the operations performed in these systems are quite stationary and repetitive, Convolutional Neural Networks (CNN), a deep learning technique, are used on the NSL-KDD dataset, a reference dataset used for the implementation of intrusion detection systems. The performance of the approach is presented and compared to some previous works. The metrics used include the percentage of correct classification, accuracy and false positives show that the proposed approach improves the performance of previous systems. 108 pp. Englisch. Codice articolo 9786205985717
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Intrusion Detection System based on deep learning
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Intrusion Detection System based on deep learning
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Intrusion Detection System based on deep learning
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Momo Ziazet JuniorJunior Momo Ziazet, Design Engineer in Telecommunications and ICT from the Faculty of Industrial Engineering of the University of Douala in Cameroon. Passionate about digital and artificial intelligence. Currently a. Codice articolo 872178853
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Intrusion Detection System based on deep learning
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Our Knowledge Publishing Mai 2023, 2023
ISBN 10: 6205985713
ISBN 13: 9786205985717
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This work focuses on the development of a new approach based on deep learning to implement an efficient and flexible intrusion detection system using the behavioral approach and mainly intended for critical infrastructures and industrial control systems. Based on the assumption that modeling the normal network behavior of industrial control systems is feasible and reliable, because the operations performed in these systems are quite stationary and repetitive, Convolutional Neural Networks (CNN), a deep learning technique, are used on the NSL-KDD dataset, a reference dataset used for the implementation of intrusion detection systems. The performance of the approach is presented and compared to some previous works. The metrics used include the percentage of correct classification, accuracy and false positives show that the proposed approach improves the performance of previous systems.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 108 pp. Englisch. Codice articolo 9786205985717
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Intrusion Detection System based on deep learning
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Taschenbuch. Condizione: Neu. Intrusion Detection System based on deep learning | Junior Momo Ziazet | Taschenbuch | Englisch | 2023 | Our Knowledge Publishing | EAN 9786205985717 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Codice articolo 126912301
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Intrusion Detection System based on deep learning
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Our Knowledge Publishing, 2023
ISBN 10: 6205985713
ISBN 13: 9786205985717
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This work focuses on the development of a new approach based on deep learning to implement an efficient and flexible intrusion detection system using the behavioral approach and mainly intended for critical infrastructures and industrial control systems. Based on the assumption that modeling the normal network behavior of industrial control systems is feasible and reliable, because the operations performed in these systems are quite stationary and repetitive, Convolutional Neural Networks (CNN), a deep learning technique, are used on the NSL-KDD dataset, a reference dataset used for the implementation of intrusion detection systems. The performance of the approach is presented and compared to some previous works. The metrics used include the percentage of correct classification, accuracy and false positives show that the proposed approach improves the performance of previous systems. Codice articolo 9786205985717
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Intrusion Detection System based on deep learning
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paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book. Codice articolo ERICA80062059857136
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