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MixNN: Protection of Federated Learning Against Inference Attacks by Mixing Neural Network Layers

Antoine Boutet 1 Thomas Lebrun 1 Jan Aalmoes 1 Adrien Baud 1 
1 PRIVATICS - Privacy Models, Architectures and Tools for the Information Society
Inria Grenoble - Rhône-Alpes, CITI - CITI Centre of Innovation in Telecommunications and Integration of services, Inria Lyon
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https://hal.inria.fr/hal-03354724
Contributor : Antoine Boutet Connect in order to contact the contributor
Submitted on : Sunday, September 26, 2021 - 6:34:56 AM
Last modification on : Thursday, August 4, 2022 - 5:18:38 PM
Long-term archiving on: : Monday, December 27, 2021 - 6:04:26 PM

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  • HAL Id : hal-03354724, version 1

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Antoine Boutet, Thomas Lebrun, Jan Aalmoes, Adrien Baud. MixNN: Protection of Federated Learning Against Inference Attacks by Mixing Neural Network Layers. [Research Report] RR-9411, INRIA Grenoble. 2021, pp.1-21. ⟨hal-03354724⟩

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