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  • Security and Resilience in Distributed Machine Learning

    Challenges, Techniques, and Future Directions

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    This book offers a comprehensive exploration of federated learning (FL), a novel approach to decentralized, privacy-preserving machine learning. This book delves into the resilience and security challenges inherent to FL, such as model poisoning and malicious attacks, that jeopardize system integrity. Through cutting-edge research and practical insights, the book introduces defense mechanisms like ... Leer más

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  • Algorithms and Architectures for Parallel Processing

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  • Handbook of Trustworthy Federated Learning

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    This handbook aims to serve as a one-stop, reliable resource, including curated surveys and expository contributions on federated learning. It covers a comprehensive range of topics, providing the reader with technical and non-technical fundamentals, applications, and extensive details of various topics. The readership spans from researchers and academics to practitioners who are deeply engaged or ... Leer más

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    This four-volume set LNISCT 687-690 constitutes the proceedings of the 21st EAI International Conference on Security and Privacy in Communication Networks, SecureComm 2025, held in Xiangtan, China, during July 4 - 6, 2025.The 119 full papers included in these volumes were carefully reviewed and selected from 341 submissions. They are organized in the following topical sections:Part I: Distributed ... Leer más

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