Journal article
Algorithms that remember: model inversion attacks and data protection law
- Abstract:
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Many individuals are concerned about the governance of machine learning systems and the prevention of algorithmic harms. The EU's recent General Data Protection Regulation (GDPR) has been seen as a core tool for achieving better governance of this area. While the GDPR does apply to the use of models in some limited situations, most of its provisions relate to the governance of personal data, while models have traditionally been seen as intellectual property. We present recent work from the in...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Version of record, pdf, 463.3KB)
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- Publisher copy:
- 10.1098/rsta.2018.0083
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Authors
Funding
+ Engineering and Physical Sciences Research Council
More from this funder
Funding agency for:
Binns, R
Grant:
EP/J017728/2
Bibliographic Details
- Publisher:
- Royal Society Publisher's website
- Journal:
- Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences Journal website
- Volume:
- 376
- Issue:
- 2133
- Article number:
- 20180083
- Publication date:
- 2018-10-15
- Acceptance date:
- 2018-07-12
- DOI:
- EISSN:
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1471-2962
- ISSN:
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1364-503X
- Source identifiers:
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935375
Item Description
- Keywords:
- Pubs id:
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pubs:935375
- UUID:
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uuid:461fa4e2-226d-4341-99ba-3640f0bd38d8
- Local pid:
- pubs:935375
- Deposit date:
- 2018-11-15
Terms of use
- Copyright holder:
- Veale et al
- Copyright date:
- 2018
- Notes:
-
Copyright © 2018 The Authors.
Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
- Licence:
- CC Attribution (CC BY)
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