We propose a decentralized privacy-preserving federated learning scheme called GAIN. GAIN blinds gradients with masks and encrypts blinded gradients.
We propose a decentralized privacy-preserving federated learning scheme called GAIN. GAIN blinds gradients with masks and encrypts blinded gradients.
Nov 1, 2023 · Federated learning enables multiple participants to cooperatively train a model, where each participant computes gradients on its data and a ...
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This paper presents DeTrust-FL, an efficient privacy-preserving federated learning framework for addressing the lack of transparency that enables isolation ...
Privacy-Preserving Federated Learning. Existing decentralized privacy-preserving techniques have been widely explored within FL, including MPC [5], [28], ...
Nov 2, 2024 · An efficient approach for privacy preserving decentralized deep learning models based on secure multi-party computation. Neurocomputing, 422 ...
Privacy-Preserving and Reliable Decentralized Federated Learning
www.computer.org › journal › 2023/04
A privacy-preserving and reliable decentralized FL scheme, designed to support batch joining/leaving of clients while incurring minimal delay and achieving ...
Missing: GAIN: | Show results with:GAIN:
Jun 22, 2024 · Federated learning is a decentralized approach to machine learning where models are trained across multiple devices (clients), such as smartphones or IoT ...
Missing: GAIN: | Show results with:GAIN:
In this proposal, we aim to design a blockchain-based data sharing and training platform, that allows participants to contribute data and train models in a ...
Missing: GAIN: | Show results with:GAIN:
GAIN: Decentralized Privacy-Preserving Federated Learning. https://doi.org/10.1016/j.jisa.2023.103615. Journal: Journal of Information Security and ...