Integrating Federated Learning for Edge Intelligence in Cybersecurity and Cloud Computing

Abstract

The fusion of Federated Learning and Edge Computing has opened up new horizons for intelligent, secure, and efficient data processing. This chapter provides an in-depth exploration of “Federated Learning for Edge Intelligence.” It explores into the fusion of decentralized machine learning with edge devices, highlighting the important aspects of privacy protection and real-time data analysis. The chapter examines the components, workflows, and practical applications of this transformative technology. The real-world use cases presented discuss how this technology is already revolutionizing industries like healthcare and predictive maintenance. Furthermore, the chapter also explores the challenges and considerations in deploying Federated Learning at the edge.