Big data analytics in fog-enabled IoT networks towards a privacy and security perspective / edited by Govind P. Gupta, Rakesh Tripathi, Brij B. Gupta and Kwok Tai Chui.

Format Electronic
EditionFirst edition.
Publication InfoBoca Raton : CRC Press, Taylor & Francis Group, 2023.
Description1 online resource
Supplemental ContentFull text available from eBooks on EBSCOhost
Supplemental ContentFull text available from Taylor & Francis eBooks
Subjects

Other author/creatorGupta, Govind P., 1979-
Other author/creatorTripathi, Rakesh.
Other author/creatorGupta, Brij, 1982-
Other author/creatorChui, Kwok Tai.
Abstract "Integration of Fog computing with the resource limited IoT network, formulate the concept of Fog-enabled IoT system. Due to large number of deployments of IoT devices, a IoT is a main source of Big data and a very high volume of sensing data is generated by IoT system such as smart cities and smart grid applications. To provide a fast and efficient data analytics solution for Fog-enabled IoT system is a very fundamental research issue. This book focus on Big data Analytics in Fog-enabled-IoT system and provides a comprehensive collection of chapters that are touches different issues related to Healthcare system, Cyber threat detection, Malware detection, security and privacy of big IoT data and IoT network. This book emphasizes and facilitate a greater understanding of various security and privacy approaches using the advance AI and Big data technologies like machine/deep learning, federated learning, blockchain, edge computing and the countermeasures to overcome the vulnerabilities of the Fog-enabled IoT system"-- Provided by publisher.
Bibliography noteIncludes bibliographical references and index.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Source of descriptionDescription based on print version record and CIP data provided by publisher.
Issued in other formPrint version: Big data analytics in fog-enabled IoT networks First edition. Boca Raton : CRC Press, 2023 9781032206448
Genre/formElectronic books.
LCCN 2022049028
ISBN9781000861860 (epub)
ISBN9781003264545 (ebook)
ISBN(hardback)
ISBN(paperback)

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