Privacy Profiles and Amplification by Subsampling
Differential privacy provides a robust quantifiable methodology to measure and control the privacy leakage of data analysis algorithms. A fundamental insight is that by forcing algorithms to be randomized, their privacy leakage can be characterized by measuring the dissimilarity between output dist...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Labor Dynamics Institute
2020-01-01
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| Series: | The Journal of Privacy and Confidentiality |
| Subjects: | |
| Online Access: | https://journalprivacyconfidentiality.org/index.php/jpc/article/view/726 |