Privacy Preserving Machine Learning: Threats and Solutions

Mohammad Al-Rubaie; J. Morris Chang

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arXiv · 1804.11238

Privacy Preserving Machine Learning: Threats and Solutions

Mohammad Al-Rubaie·J. Morris Chang

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Abstract

For privacy concerns to be addressed adequately in current machine learning systems, the knowledge gap between the machine learning and privacy communities must be bridged. This article aims to provide an introduction to the intersection of both fields with special emphasis on the techniques used to protect the data.

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Mohammad Al-Rubaie, J. Morris Chang. 2018-03-27. Privacy Preserving Machine Learning: Threats and Solutions. https://arxiv.org/abs/1804.11238

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