9786206739449 - Deep Learning Based Intrusion Detection Framework in Industrial IoT de K V, Raghavender; DURGA BHAVANI, B. (8 resultados)

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Taschenbuch. Condición: 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.

Condición: 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.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. 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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 56 pp. Englisch.

Taschenbuch. Condición: 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.

Taschenbuch. Condición: 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 Print on Demand.