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Publicado por Springer-Nature New York Inc, 2020
ISBN 10: 9811565740 ISBN 13: 9789811565748
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Añadir al carritoTaschenbuch. Condición: Neu. Accountability and Privacy in Network Security | Yuxiang Ma (u. a.) | Taschenbuch | xii | Englisch | 2020 | Springer | EAN 9789811565748 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book discusses accountability and privacy in network security from a technical perspective, providing a comprehensive overview of the latest research, as well as the current challenges and open issues. Further, it proposes a set of new and innovative solutions to balance privacy and accountability in networks in terms of their content, flow and service, using practical deep learning techniques for encrypted traffic analysis and focusing on the application of new technologies and concepts. These solutions take into account various key components (e.g. the in-network cache) in network architectures and adopt the emerging blockchain technique to ensure the security and scalability of the proposed architectures. In addition, the book examines in detail related studies on accountability and privacy, and validates the architectures using real-world datasets. Presenting secure and scalable solutions that can detect malicious behaviors in the networkin a timely manner without compromising user privacy, the book offers a valuable resource for undergraduate and graduate students, researchers, and engineers working in the fields of network architecture and cybersecurity.
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Publicado por Springer Nature Singapore Sep 2020, 2020
ISBN 10: 9811565740 ISBN 13: 9789811565748
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book discusses accountability and privacy in network security from a technical perspective, providing a comprehensive overview of the latest research, as well as the current challenges and open issues. Further, it proposes a set of new and innovative solutions to balance privacy and accountability in networks in terms of their content, flow and service, using practical deep learning techniques for encrypted traffic analysis and focusing on the application of new technologies and concepts. These solutions take into account various key components (e.g. the in-network cache) in network architectures and adopt the emerging blockchain technique to ensure the security and scalability of the proposed architectures. In addition, the book examines in detail related studies on accountability and privacy, and validates the architectures using real-world datasets. Presenting secure and scalable solutions that can detect malicious behaviors in the network in a timely manner without compromising user privacy, the book offers a valuable resource for undergraduate and graduate students, researchers, and engineers working in the fields of network architecture and cybersecurity. 152 pp. Englisch.
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Discusses accountability and privacy from a technical perspective, describing typical application scenarios and emerging network technologies/architectures   Can be used for teaching undergraduate/graduate courses, off.
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Añadir al carritoCondición: New. Print on Demand pp. XII, 140 62 illus., 59 illus. in color.
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Añadir al carritoCondición: New. PRINT ON DEMAND pp. XII, 140 62 illus., 59 illus. in color.
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Publicado por Springer, Springer Sep 2020, 2020
ISBN 10: 9811565740 ISBN 13: 9789811565748
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book discusses accountability and privacy in network security from a technical perspective, providing a comprehensive overview of the latest research, as well as the current challenges and open issues. Further, it proposes a set of new and innovative solutions to balance privacy and accountability in networks in terms of their content, flow and service, using practical deep learning techniques for encrypted traffic analysis and focusing on the application of new technologies and concepts. These solutions take into account various key components (e.g. the in-network cache) in network architectures and adopt the emerging blockchain technique to ensure the security and scalability of the proposed architectures. In addition, the book examines in detail related studies on accountability and privacy, and validates the architectures using real-world datasets.Presenting secure and scalable solutions that can detect malicious behaviors in the networkin a timely manner without compromising user privacy, the book offers a valuable resource for undergraduate and graduate students, researchers, and engineers working in the fields of network architecture and cybersecurity.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 152 pp. Englisch.