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 ...
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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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