Convergence of Blockchain, Internet of Everything, and Federated Learning for Security (Premier Research Source) - Hardcover

Hardcover

ISBN 13: 9798337314242

Verlag: IGI Global, 2025

Inhaltsangabe

The convergence of blockchain, the Internet of Everything (IoE), and federated learning paves the way for enhanced security in digital ecosystems. Blockchain offers decentralized, tamper-proof solutions that ensure data integrity, while the IoE connects smart devices, generating large amounts of data that require robust protection. Federated learning allows models to be trained locally on edge devices without transferring sensitive data to centralized servers, minimizing exposure to cyber threats. These technologies strengthen privacy and data security while enabling more efficient, scalable, and resilient systems. Further research into the potential of these technologies may redefine how security is managed, ensuring a safer environment for individuals and organizations. Convergence of Blockchain, Internet of Everything, and Federated Learning for Security explores the convergence of blockchain, IoEs, federated learning, and cybersecurity, highlighting their relevance in the modern digital landscape. It examines the importance of these technologies in addressing security challenges and enhancing data privacy in interconnected systems. This book covers topics such as cryptography, machine learning, and smart grids, and is a useful resource for business owners, computer engineers, data scientists, academicians, and researchers.

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Über die Autorinnen und Autoren

Fasee Ullah is currently working as an Associate Professor with the Department of Computing, Universiti Teknologi PETRONAS, Seri Iskandar, Perak Darul Ridzuan, Malaysia. He received a Ph.D. degree from the Faculty of Computing, Universiti Teknologi Malaysia (UTM), Malaysia. He has also completed the postdoctoral fellowship from the University of Macau, Macao, the academic talented program of the Government of Macau. He has published many research papers in reputed impact factor journals and conferences. He was a recipient of the Chancellor Award and the Best Student Award at UTM during his Ph.D. degree. His research interests include cloud security, cybersecurity, Computer Forensics, information security, smart hash security designing, cognitive smart cities, big data analytics, WBAN, deep learning, and IoT. He is currently providing reviewing services to IEEE Transactions journals, IEEE Access, ACM, Scientific Reports, and so on.

Arfat Ahmad Khan received the B.Eng. de- gree in electrical engineering from the University of Lahore, Pakistan, in 2013, the M.Eng. degree in electrical engineering from the Government College University Lahore, Pakistan, in 2015, and the Ph.D. degree in telecommunication and com- puter engineering from the Suranaree University of Technology, Thailand, in 2018. From 2014 to 2016, he was an RF Engineer with Etisalat, United Arab Emirates. From 2018 to 2022, he worked as a Lecturer and a Senior Researcher with the Suranaree University of Technology. He is currently working as a Senior Lecturer and a Researcher at Khon Kaen University, Thailand. He has published more than 50 high impact factored research articles in reputed journals, such as IEEE transactions, Elsevier, etc. His research interests include optimization and stochastic pro- cesses, wireless sensor networks, Machine, deep and federated learning for intelligent systems, such as Agriculture, Internet Security, Image processing, etc., and the advance wireless communications.

Asad Ullah Dedicated and accomplished computer science professional with expertise in Artificial Intelligence. Adept at conducting cutting-edge research, delivering engaging lectures, and mentoring students to foster their academic and professional growth. Committed to advancing the field of computer science through innovative research contributions and educational excellence. Proven leadership abilities in academic administration and collaborative research initiatives.

Details zur Ausgabe

• Verlag: IGI Global
• Erscheinungsdatum: 2025
• Sprache: Englisch
• ISBN 13: 9798337314242
• Einband: Gebundene Ausgabe
• Anzahl der Seiten: 496
• Herausgeber: Ullah Fasee, Ahmad Khan Arfat, Ullah Asad
• Kontakt zum Hersteller: preigu GmbH & Co. KG; mail@preigu.de; ; Lengericher Landstr. 19; Osnabrück; Niedersachsen; 49078; Deutschland