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Sep 4, 2024 · We propose FedGT, a novel framework for identifying malicious clients in federated learning with secure aggregation. Inspired by group ...
May 9, 2023 · By choosing the size, number, and overlap between groups, FedGT strikes a balance between privacy and security. Specifically, the server learns ...
By choosing the size, number, and overlap between groups, FedGT strikes a balance between privacy and security. Specifically, the server learns the aggregated ...
Balancing Privacy and Security in Federated Learning with FedGT: A Group Testing Framework. M Xhemrishi, J Östman, A Wachter-Zeh, AG i Amat. arXiv preprint ...
By choosing the size, number, and overlap between groups, FedGT strikes a balance between privacy and security. Specifically, the server learns the aggregated ...
By choosing the size, number, and overlap between groups, FedGT strikes a balance between privacy and security. Specifically, the server learns the aggregated.
May 17, 2024 · Federated learning (FL) as a novel paradigm in Artificial Intelligence (AI), ensures enhanced privacy by eliminating data centralization and ...
Missing: FedGT: | Show results with:FedGT:
May 27, 2024 · PDF | On May 1, 2024, Samaneh Mohammadi and others published Balancing Privacy and Performance in Federated Learning: a Systematic ...
Missing: FedGT: | Show results with:FedGT:
Aug 11, 2024 · One of the proposed solutions is to decentralize learning by allowing each device to train a model locally on its own data without sharing it.
Missing: FedGT: | Show results with:FedGT:
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To bolster data security during this process, FL algorithms frequently employ a differential privacy (DP) mechanism that introduces noise into each client's ...
Missing: FedGT: Group Testing