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SoK: Differential Privacies by Damien Desfontaines, Balázs Pejó. 2019.
SoK: Differential Privacies by Damien Desfontaines, Balázs Pejó. 2019.
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==References==
{{Reflist|refs=
<ref name="DKMMN06">
Dwork, Cynthia, Krishnaram Kenthapadi, Frank McSherry, Ilya Mironov, and Moni Naor. "Our data, ourselves: Privacy via distributed noise generation." In Advances in Cryptology-EUROCRYPT 2006, pp. 486–503. Springer Berlin Heidelberg, 2006.</ref>
<!-- unused refs <ref name="CABP13">
Chatzikokolakis, Konstantinos, Miguel E. Andrés, Nicolás Emilio Bordenabe, and Catuscia Palamidessi. "Broadening the scope of Differential Privacy using metrics." In Privacy Enhancing Technologies, pp. 82–102. Springer Berlin Heidelberg, 2013.</ref>
<ref name="HRW11">
Hall, Rob, Alessandro Rinaldo, and Larry Wasserman. "Random differential privacy." arXiv preprint arXiv:1112.2680 (2011).</ref>-->
<ref name="MachanavajjhalaKAGV08">
Ashwin Machanavajjhala, Daniel Kifer, John M. Abowd, Johannes Gehrke, and Lars Vilhuber. "Privacy: Theory meets Practice on the Map". In Proceedings of the 24th International Conference on Data Engineering, ICDE) 2008.</ref>
<ref name="RAPPOR">
Úlfar Erlingsson, Vasyl Pihur, Aleksandra Korolova. [https://dl.acm.org/doi/10.1145/2660267.2660348 "RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response".] In Proceedings of the 21st ACM Conference on Computer and Communications Security (CCS), 2014. {{doi|10.1145/2660267.2660348}}</ref>
<ref name="DMNS06">
[https://link.springer.com/chapter/10.1007%2F11681878_14 Calibrating Noise to Sensitivity in Private Data Analysis] by Cynthia Dwork, Frank McSherry, Kobbi Nissim, Adam Smith. In Theory of Cryptography Conference (TCC), Springer, 2006. {{doi|10.1007/11681878_14}}. The [https://journalprivacyconfidentiality.org/index.php/jpc/article/view/405 full version] appears in Journal of Privacy and Confidentiality, 7 (3), 17-51. {{doi|10.29012/jpc.v7i3.405}}</ref>
<ref name="PINQ">
[http://research.microsoft.com/pubs/80218/sigmod115-mcsherry.pdf Privacy integrated queries: an extensible platform for privacy-preserving data analysis] by Frank D. McSherry. In Proceedings of the 35th SIGMOD International Conference on Management of Data (SIGMOD), 2009. {{doi|10.1145/1559845.1559850}}</ref>
<ref name="Dwork, ICALP 2006">
[http://research.microsoft.com/pubs/64346/dwork.pdf Differential Privacy] by Cynthia Dwork, International Colloquium on Automata, Languages and Programming (ICALP) 2006, p. 1–12. {{doi|10.1007/11787006 1}}</ref>
<ref name="DPBook">
[http://www.cis.upenn.edu/~aaroth/Papers/privacybook.pdf The Algorithmic Foundations of Differential Privacy] by Cynthia Dwork and Aaron Roth. Foundations and Trends in Theoretical Computer Science. Vol. 9, no. 3–4, pp. 211‐407, Aug. 2014. {{doi|10.1561/0400000042}}</ref>
<ref name="Eland">[https://europe.googleblog.com/2015/11/tackling-urban-mobility-with-technology.html Tackling Urban Mobility with Technology] by Andrew Eland. Google Policy Europe Blog, Nov 18, 2015.</ref>
<ref name="DpWinTelemetry">[https://www.microsoft.com/en-us/research/publication/collecting-telemetry-data-privately/ Collecting telemetry data privately] by Bolin Ding, Jana Kulkarni, Sergey Yekhanin. NIPS 2017.</ref>
<ref name="DpLinkedIn">[https://arxiv.org/abs/2002.05839 LinkedIn's Audience Engagements API: A Privacy Preserving Data Analytics System at Scale] by Ryan Rogers, Subbu Subramaniam, Sean Peng, David Durfee, Seunghyun Lee, Santosh Kumar Kancha, Shraddha Sahay, Parvez Ahammad. arXiv:2002.05839.</ref>
<ref name="DP19">[https://arxiv.org/abs/1906.01337 SoK: Differential Privacies] by Damien Desfontaines, Balázs Pejó. 2019.</ref>
}}
}}