De Cristofaro, E;
(2021)
A Critical Overview of Privacy in Machine Learning.
IEEE Security and Privacy
, 19
(4)
pp. 19-27.
10.1109/MSEC.2021.3076443.
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Abstract
This article reviews privacy challenges in machine learning and provides a critical overview of the relevant research literature. The possible adversarial models are discussed, a wide range of attacks related to sensitive information leakage is covered, and several open problems are highlighted.
| Type: | Article |
|---|---|
| Title: | A Critical Overview of Privacy in Machine Learning |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/MSEC.2021.3076443 |
| Publisher version: | https://doi.org/10.1109/MSEC.2021.3076443 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10132108 |
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