List of components and paper references

[raprasad]

• [ ] Add to component docs
• [ ] Possible attached field for the citation
• [ ] stub in whitenoise core
  • in the report generation

In a shared google sheet (or similar):

• List components and related paper references as appropriate (based on the implementation, etc)
  • latest components: https://opendifferentialprivacy.github.io/whitenoise-core/doc/whitenoise_validator/docs/components/index.html

[Shoeboxam]

From @ctcovington https://tworavens.slack.com/archives/CRNSFC508/p1588104720021900?thread_ts=1588095160.013400&cid=CRNSFC508

Mechanisms

• Exponential
  • McSherry & Talwar (2007) https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/mdviadp.pdf
• Gaussian
  • Dwork & Roth (2014) https://www.cis.upenn.edu/~aaroth/Papers/privacybook.pdf
• Geometric
  • Ghosh, Roughgarden, & Sundararajan (2012) https://theory.stanford.edu/~tim/papers/priv.pdf
  • If you can list two, also include Balcer & Vadhan (2017) https://arxiv.org/pdf/1709.05396.pdf
• Laplace
  • Dwork, McSherry, Nissim, & Smith (2006) https://people.csail.mit.edu/asmith/PS/sensitivity-tcc-final.pdf

DP Statistics

• DPCount
  • In my opinion, should be Ghosh, Roughgarden, & Sundararajan (2012) https://theory.stanford.edu/~tim/papers/priv.pdf
• DPCovariance
  • None
• DPHistogram
  • Ghosh, Roughgarden, & Sundararajan (2012) https://theory.stanford.edu/~tim/papers/priv.pdf
  • If you can list two, also include Balcer & Vadhan (2017) https://arxiv.org/pdf/1709.05396.pdf
• DPMaximum
  • None
• DPMean
  • Dwork, McSherry, Nissim, & Smith (2006) https://people.csail.mit.edu/asmith/PS/sensitivity-tcc-final.pdf
• DPMedian
  • Unclear, but maybe Smith (2011) http://www.cse.psu.edu/~ads22/pubs/2011/stoc194-smith.pdf
• DPMinimum
  • None
• DPMomentRaw
  • None
• DPSum
  • Dwork, McSherry, Nissim, & Smith (2006) https://people.csail.mit.edu/asmith/PS/sensitivity-tcc-final.pdf
• DPVariance
  • Unclear, maybe D'Orazio, Honaker, & King (2015) http://hona.kr/papers/files/DOrazioHonakerKingPrivacy.pdf

[Shoeboxam]

Exponential [1] Gaussian [2] Geometric [3][4] Laplace [5] DPCount [3] DPHistogram [3][4] DPMean [5] DPSum [5] DPVariance [6]

[1] F. McSherry and K. Talwar, "Mechanism Design via Differential Privacy," 48th Annual IEEE Symposium on Foundations of Computer Science (FOCS'07), Providence, RI, 2007, pp. 94-103, doi: 10.1109/FOCS.2007.66. https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/mdviadp.pdf

[2] Cynthia Dwork and Aaron Roth. 2014. The Algorithmic Foundations of Differential Privacy. Found. Trends Theor. Comput. Sci. 9, 3–4 (August 2014), 211–407. DOI:https://doi.org/10.1561/0400000042 https://www.cis.upenn.edu/~aaroth/Papers/privacybook.pdf

[3] Arpita Ghosh, Tim Roughgarden, and Mukund Sundararajan. 2009. Universally utility-maximizing privacy mechanisms. In Proceedings of the forty-first annual ACM symposium on Theory of computing (STOC '09). Association for Computing Machinery, New York, NY, USA, 351–360. DOI:https://doi.org/10.1145/1536414.1536464 https://theory.stanford.edu/~tim/papers/priv.pdf

[4] Balcer, Victor, and Salil Vadhan. 2019. “Differential Privacy on Finite Computers”. Journal of Privacy and Confidentiality 9 (2). https://doi.org/10.29012/jpc.679. https://arxiv.org/pdf/1709.05396.pdf

[5] Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith. 2006. Calibrating noise to sensitivity in private data analysis. In Proceedings of the Third conference on Theory of Cryptography (TCC'06). Springer-Verlag, Berlin, Heidelberg, 265–284. DOI:https://doi.org/10.1007/11681878_14 https://people.csail.mit.edu/asmith/PS/sensitivity-tcc-final.pdf

[6] D'Orazio, V., Honaker, J., & King, G. (2015). Differential Privacy for Social Science Inference. Alfred P. Sloan Foundation Economic Research Paper Series. http://hona.kr/papers/files/DOrazioHonakerKingPrivacy.pdf

[saniavn]

@Shoeboxam: in case you need the list of references here is the link to references back in April: https://github.com/opendifferentialprivacy/whitenoise-core/commit/b7d02dd4b42888b21fcb01a800f9be3d1399b51d?short_path=b54f825#diff-b54f825f2b86f2a31c03f7241747cf90