Privacy Preserving Machine Learning: Threats and Solutions

Authors: Mohammad Al-Rubaie, J. Morris Chang
Published: 2018-03-27

Source: https://arxiv.org/abs/1804.11238

PDF: https://arxiv.org/pdf/1804.11238

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プライバシー保護技術 次元削減手法

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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.