Privacidade diferencial (Portuguese Wikipedia)

Analysis of information sources in references of the Wikipedia article "Privacidade diferencial" in Portuguese language version.

refsWebsite

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8doi.org

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4microsoft.com

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3arxiv.org

69^th place

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1springer.com

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1journalprivacyconfidentiality.org

low place

1cornell.edu

332^nd place

526^th place

1hu-berlin.de

2,869^th place

3,582^nd place

1iacr.org

5,032^nd place

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1eatcs.org

low place

1upenn.edu

702^nd place

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1jstor.org

26^th place

65^th place

1nih.gov

4^th place

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1acm.org

1,185^th place

1,301^st place

1github.com

383^rd place

814^th place

1googleblog.com

1,272^nd place

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1apple.com

67^th place

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1privitar.com

low place

1belfercenter.org

low place

acm.org

dl.acm.org

Úlfar Erlingsson, Vasyl Pihur, Aleksandra Korolova. "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

apple.com

«Apple - Press Info - Apple Previews iOS 10, the Biggest iOS Release Ever». Apple. Consultado em 16 de junho de 2016

arxiv.org

Christos Dimitrakakis, Blaine Nelson, Aikaterini Mitrokotsa, Benjamin Rubinstein. Robust and Private Bayesian Inference. Algorithmic Learning Theory 2014
SoK: Differential Privacies by Damien Desfontaines, Balázs Pejó. 2019.
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.

belfercenter.org

«Technology Factsheet: Differential Privacy». Belfer Center for Science and International Affairs (em inglês). Consultado em 12 de abril de 2021

cornell.edu

archives.vrdc.cornell.edu

Dalenius, Tore (1977). «Towards a methodology for statistical disclosure control» (PDF). Statistik Tidskrift. 15

doi.org

dx.doi.org

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 full version appears in Journal of Privacy and Confidentiality, 7 (3), 17-51. doi:10.29012/jpc.v7i3.405
Irit Dinur and Kobbi Nissim. 2003. Revealing information while preserving privacy. In Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems (PODS '03). ACM, New York, NY, USA, 202–210. doi:10.1145/773153.773173
Dwork, Cynthia (25 de abril de 2008). «Differential Privacy: A Survey of Results». In: Agrawal, Angsheng; Du; Duan; Li. Theory and Applications of Models of Computation. Col: Lecture Notes in Computer Science (em inglês). 4978. [S.l.]: Springer Berlin Heidelberg. pp. 1–19. ISBN 9783540792277. doi:10.1007/978-3-540-79228-4_1
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
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
Differential Privacy by Cynthia Dwork, International Colloquium on Automata, Languages and Programming (ICALP) 2006, p. 1–12. doi:10.1007/11787006_1
Warner, S. L. (março de 1965). «Randomised response: a survey technique for eliminating evasive answer bias». Taylor & Francis. Journal of the American Statistical Association. 60 (309): 63–69. JSTOR 2283137. PMID 12261830. doi:10.1080/01621459.1965.10480775
Úlfar Erlingsson, Vasyl Pihur, Aleksandra Korolova. "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

eatcs.org

«2017 Gödel Prize»

github.com

google/rappor, GitHub, 15 de julho de 2021

googleblog.com

europe.googleblog.com

Tackling Urban Mobility with Technology by Andrew Eland. Google Policy Europe Blog, Nov 18, 2015.

hu-berlin.de

dbis.informatik.hu-berlin.de

Dorothy E. Denning; Peter J. Denning; Mayer D. Schwartz (março de 1978). «The Tracker: A Threat to Statistical Database Security» (PDF). 4 (1): 76–96

iacr.org

«TCC Test-of-Time Award»

journalprivacyconfidentiality.org

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 full version appears in Journal of Privacy and Confidentiality, 7 (3), 17-51. doi:10.29012/jpc.v7i3.405

jstor.org

Warner, S. L. (março de 1965). «Randomised response: a survey technique for eliminating evasive answer bias». Taylor & Francis. Journal of the American Statistical Association. 60 (309): 63–69. JSTOR 2283137. PMID 12261830. doi:10.1080/01621459.1965.10480775

microsoft.com

research.microsoft.com

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
Differential Privacy by Cynthia Dwork, International Colloquium on Automata, Languages and Programming (ICALP) 2006, p. 1–12. doi:10.1007/11787006_1
F.McSherry and K.Talwar. Mechasim Design via Differential Privacy. Proceedings of the 48th Annual Symposium of Foundations of Computer Science, 2007.

microsoft.com

Collecting telemetry data privately by Bolin Ding, Jana Kulkarni, Sergey Yekhanin. NIPS 2017.

nih.gov

ncbi.nlm.nih.gov

Warner, S. L. (março de 1965). «Randomised response: a survey technique for eliminating evasive answer bias». Taylor & Francis. Journal of the American Statistical Association. 60 (309): 63–69. JSTOR 2283137. PMID 12261830. doi:10.1080/01621459.1965.10480775

privitar.com

«Privitar Lens». Consultado em 20 de fevereiro de 2018

springer.com

link.springer.com

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 full version appears in Journal of Privacy and Confidentiality, 7 (3), 17-51. doi:10.29012/jpc.v7i3.405

upenn.edu

cis.upenn.edu

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