ML Privacy Meter: Aiding Regulatory Compliance by Quantifying the Privacy Risks of Machine Learning

Workshop on Hot Topics in Privacy Enhancing Technologies (HotPETs)

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Bibliographic Details
Main Authors:	Murakonda, Sasi Kumar, Shokri Reza
Other Authors:	DEPARTMENT OF COMPUTER SCIENCE
Format:	Conference or Workshop Item
Published:	2020
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/176521
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Institution:	National University of Singapore

id	sg-nus-scholar.10635-176521
record_format	dspace
spelling	sg-nus-scholar.10635-1765212024-11-10T20:14:07Z ML Privacy Meter: Aiding Regulatory Compliance by Quantifying the Privacy Risks of Machine Learning Murakonda, Sasi Kumar Shokri Reza DEPARTMENT OF COMPUTER SCIENCE Dr Shokri Reza Workshop on Hot Topics in Privacy Enhancing Technologies (HotPETs) 2020-09-23T00:59:34Z 2020-09-23T00:59:34Z 2020-07-17 2020-09-22T10:18:19Z Conference Paper Murakonda, Sasi Kumar, Shokri Reza (2020-07-17). ML Privacy Meter: Aiding Regulatory Compliance by Quantifying the Privacy Risks of Machine Learning. Workshop on Hot Topics in Privacy Enhancing Technologies (HotPETs). ScholarBank@NUS Repository. https://scholarbank.nus.edu.sg/handle/10635/176521 Elements
institution	National University of Singapore
building	NUS Library
continent	Asia
country	Singapore Singapore
content_provider	NUS Library
collection	ScholarBank@NUS
description	Workshop on Hot Topics in Privacy Enhancing Technologies (HotPETs)
author2	DEPARTMENT OF COMPUTER SCIENCE
author_facet	DEPARTMENT OF COMPUTER SCIENCE Murakonda, Sasi Kumar Shokri Reza
format	Conference or Workshop Item
author	Murakonda, Sasi Kumar Shokri Reza
spellingShingle	Murakonda, Sasi Kumar Shokri Reza ML Privacy Meter: Aiding Regulatory Compliance by Quantifying the Privacy Risks of Machine Learning
author_sort	Murakonda, Sasi Kumar
title	ML Privacy Meter: Aiding Regulatory Compliance by Quantifying the Privacy Risks of Machine Learning
title_short	ML Privacy Meter: Aiding Regulatory Compliance by Quantifying the Privacy Risks of Machine Learning
title_full	ML Privacy Meter: Aiding Regulatory Compliance by Quantifying the Privacy Risks of Machine Learning
title_fullStr	ML Privacy Meter: Aiding Regulatory Compliance by Quantifying the Privacy Risks of Machine Learning
title_full_unstemmed	ML Privacy Meter: Aiding Regulatory Compliance by Quantifying the Privacy Risks of Machine Learning
title_sort	ml privacy meter: aiding regulatory compliance by quantifying the privacy risks of machine learning
publishDate	2020
url	https://scholarbank.nus.edu.sg/handle/10635/176521
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ML Privacy Meter: Aiding Regulatory Compliance by Quantifying the Privacy Risks of Machine Learning

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