Privacy-Preserving Distributed Learning Framework for 6G Telecom Ecosystems

Pooyan Safari; Behnam Shariati; Johannes Karl Fischer

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arXiv · 2008.07225

Privacy-Preserving Distributed Learning Framework for 6G Telecom Ecosystems

Pooyan Safari·Behnam Shariati·Johannes Karl Fischer

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Abstract

We present a privacy-preserving distributed learning framework for telecom ecosystems in the 6G-era that enables the vision of shared ownership and governance of ML models, while protecting the privacy of the data owners. We demonstrate its benefits by applying it to the use-case of Quality of Transmission (QoT) estimation in multi-domain multi-vendor optical networks, where no data of individual domains is shared with the network management system (NMS).

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Pooyan Safari, Behnam Shariati, Johannes Karl Fischer. 2020-08-17. Privacy-Preserving Distributed Learning Framework for 6G Telecom Ecosystems. https://arxiv.org/abs/2008.07225

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