Verified Commit 1ca572cf authored by Martin Isaksson's avatar Martin Isaksson
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Add embedded video for Sec. FL.

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---
title: Secure Federated Learning in 5G Mobile Networks
author: M. Isaksson, K. Norrman
in: To appear in Arxiv
tags:
- federated learning-
- machine learning-
- security protocol
- privacy
date: 2019-09-28
online: https://arxiv.org/
bibtex: |
@misc{8369000,
author={Isaksson, Martin and Norrman, Karl},
title={Secure Federated Learning in 5G Mobile Networks},
year={2019},
volume={},
number={},
}
image:
path: /images/network.jpg
---
Machine Learning is an important enabler for
optimizing, securing and managing mobile networks. This leads to increased
collection and processing of data from network functions, which in turn may
leak sensitive information about end-users. Consequently, mechanisms to
protect the privacy of end-users are needed. We seamlessly
integrate Federated Learning into the 3GPP 5G Network Data Analytics
framework, and add a multi-party computation protocol for protecting the
confidentiality of local updates. We also outline how our work can be fitted
into the WARA-PS research arena.
<iframe width="800" height="450" src="https://www.youtube.com/embed/JmuZcVAtLKY" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
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