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Privacy Preserving Machine Learning: Threats and Solutions
March 27, 2018 Β· Declared Dead Β· π IEEE Security and Privacy
"No code URL or promise found in abstract"
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Authors
Mohammad Al-Rubaie, J. Morris Chang
arXiv ID
1804.11238
Category
cs.CR: Cryptography & Security
Cross-listed
cs.LG
Citations
402
Venue
IEEE Security and Privacy
Last Checked
3 months ago
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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