A Deep Learning Based Intrusion Detection Framework in Industrial IoT is a sophisticated system designed to safeguard critical infrastructure from unauthorized access and malicious activities. Leveraging the power of deep learning algorithms, this framework utilizes advanced neural networks to analyze vast amounts of data collected from Industrial Internet of Things (IoT) devices. By training the deep learning models on labeled datasets consisting of normal and anomalous behavior patterns, the framework can accurately identify and classify various types of intrusions in real-time. The framework's ability to adapt and learn from evolving threats makes it an effective defense mechanism, providing a robust security layer for industrial IoT environments, ensuring the integrity, availability, and confidentiality of critical assets and systems.
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Dr. Raghavender K V ist außerordentlicher Professor in der Abteilung für CSE am G. Narayanamma Institute of Technology & Science, Hyderabad. Er hat einen Doktortitel in Informatik und Ingenieurwesen mit den Schwerpunkten Netzwerksicherheit und maschinelles Lernen. Er hat seinen M.Tech und B.Tech in CSE an der JNTUH, Hyderabad, Telangana, Indien abgeschlossen.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A Deep Learning Based Intrusion Detection Framework in Industrial IoT is a sophisticated system designed to safeguard critical infrastructure from unauthorized access and malicious activities. Leveraging the power of deep learning algorithms, this framework utilizes advanced neural networks to analyze vast amounts of data collected from Industrial Internet of Things (IoT) devices. By training the deep learning models on labeled datasets consisting of normal and anomalous behavior patterns, the framework can accurately identify and classify various types of intrusions in real-time. The framework's ability to adapt and learn from evolving threats makes it an effective defense mechanism, providing a robust security layer for industrial IoT environments, ensuring the integrity, availability, and confidentiality of critical assets and systems. 56 pp. Englisch. Bestandsnummer des Verkäufers 9786206739449
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. A Deep Learning Based Intrusion Detection Framework in Industrial IoT is a sophisticated system designed to safeguard critical infrastructure from unauthorized access and malicious activities. Leveraging the power of deep learning algorithms, this framework. Bestandsnummer des Verkäufers 1022526332
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Taschenbuch. Zustand: Neu. Neuware -A Deep Learning Based Intrusion Detection Framework in Industrial IoT is a sophisticated system designed to safeguard critical infrastructure from unauthorized access and malicious activities. Leveraging the power of deep learning algorithms, this framework utilizes advanced neural networks to analyze vast amounts of data collected from Industrial Internet of Things (IoT) devices. By training the deep learning models on labeled datasets consisting of normal and anomalous behavior patterns, the framework can accurately identify and classify various types of intrusions in real-time. The framework's ability to adapt and learn from evolving threats makes it an effective defense mechanism, providing a robust security layer for industrial IoT environments, ensuring the integrity, availability, and confidentiality of critical assets and systems.Books on Demand GmbH, Überseering 33, 22297 Hamburg 56 pp. Englisch. Bestandsnummer des Verkäufers 9786206739449
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - A Deep Learning Based Intrusion Detection Framework in Industrial IoT is a sophisticated system designed to safeguard critical infrastructure from unauthorized access and malicious activities. Leveraging the power of deep learning algorithms, this framework utilizes advanced neural networks to analyze vast amounts of data collected from Industrial Internet of Things (IoT) devices. By training the deep learning models on labeled datasets consisting of normal and anomalous behavior patterns, the framework can accurately identify and classify various types of intrusions in real-time. The framework's ability to adapt and learn from evolving threats makes it an effective defense mechanism, providing a robust security layer for industrial IoT environments, ensuring the integrity, availability, and confidentiality of critical assets and systems. Bestandsnummer des Verkäufers 9786206739449
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Taschenbuch. Zustand: Neu. Deep Learning Based Intrusion Detection Framework in Industrial IoT | Raghavender K V (u. a.) | Taschenbuch | Englisch | 2023 | LAP LAMBERT Academic Publishing | EAN 9786206739449 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 127344133
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