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4 articles for “secure aggregation (SA)”
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An Adaptive and Privacy-Aware Federated Learning Framework for Efficient and Secure Model Training Across Heterogeneous Datasets
Abstract: The problem of efficiency and privacy regarding heterogeneous data in modern distributed machine learning systems is a vital point that should be taken into account. The absence of IID data distribution, client heterogeneity, and privacy invasion during the aggregation model are the bane of conventional federated learning (FL) approaches to learning like FedAvg and FedProx. The paper proposes that the adaptive and privacy-aware FL framework (AFL-P) can be used to …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 16–25 Read article
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Federated Learning for Energy Management in Next Generation Smart Cities
Abstract: Federated learning has emerged as a promising approach for addressing the challenges of energy management in next-generation smart cities. This decentralized approach to machine learning allows collaborative model training among distributed data sources, while safeguarding data privacy and security. In this study, we explore the application of federated learning techniques to optimize energy consumption, enhance grid stability, and promote sustainability in smart city environments. By aggregating data from diverse sources …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 1, 2024 · pp. 19–27 Read article
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Interior Design for Disaster Resilience
Abstract: In the age of heightening environment actuated calamities and the thriving intricacy of metropolitan scenes, the basic to implant catastrophe flexibility inside plan resounds with remarkable criticalness. This examination paper embraces a general odyssey, diving into the complicated interchange between inside plan and catastrophe flexibility inside the constructed climate. Drawing upon a tremendous embroidery of insightful writing, exact investigations, and genuine models, the paper fastidiously disentangles the multi-layered methodologies, developments, …
Published in International Journal of Climate Conditions · Vol. 1, Issue 1, 2024 · pp. 01–15 Read article
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Searchable Encryption Based on Key Aggregation
Abstract: The ability to selectively distribute data with individuals in public cloud services may alleviate safety concerns about inadvertent privacy violations in cloud storage. The need for flexibility in sharing specific sets of documents with various user groups requires the use of distinct encryption keys for each document. This undertaking tackles practical difficulties by presenting the notion of Key-Aggregate Searchable Encryption (KASE). Natural language processing was used to extract essential phrases …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 1, 2024 · pp. 21–25 Read article