Difference between revisions of "Differential privacy"

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A few references on Differential Privacy, for people who don't want to get bogged down with the math.
A few references on Differential Privacy, for people who don't want to get bogged down with the math.


* [https://www.cis.upenn.edu/~aaroth/Papers/privacybook.pdf The Algorithmic Foundations of Differential Privacy], a textbook by Cynthia Dwork and Aaron Roth. The first two chapters are understable by a person who doesn't have an advanced degree in mathematics or cryptography, and it's free!
* [https://www.cis.upenn.edu/~aaroth/Papers/privacybook.pdf The Algorithmic Foundations of Differential Privacy] (2014), a textbook by Cynthia Dwork and Aaron Roth. The first two chapters are understable by a person who doesn't have an advanced degree in mathematics or cryptography, and it's free!


* Frank McSherry's blog post, [https://github.com/frankmcsherry/blog/blob/master/posts/2016-02-03.md Differential privacy for dummies.]
* Frank McSherry's blog post, [https://github.com/frankmcsherry/blog/blob/master/posts/2016-02-03.md Differential privacy for dummies.] (2016)


* [https://research.neustar.biz/2014/09/08/differential-privacy-the-basics/ Introductory article by Anthony Tockar], the neustar intern who was behind the re-identificaton of the 2013 NYC taxi data release.
* [https://research.neustar.biz/2014/09/08/differential-privacy-the-basics/ Introductory article by Anthony Tockar], the neustar intern who was behind the re-identificaton of the 2013 NYC taxi data release. (2014)


* [http://dimacs.rutgers.edu/~graham/pubs/slides/privdb-tutorial.pdf Building Blocks of Privacy: Differentially Private Mechanisms], Graham Cormode
* [http://dimacs.rutgers.edu/~graham/pubs/slides/privdb-tutorial.pdf Building Blocks of Privacy: Differentially Private Mechanisms] (2013), Graham Cormode


== Video ==
== Video ==

Revision as of 10:44, 15 January 2018

A few references on Differential Privacy, for people who don't want to get bogged down with the math.

Video

Applications

Advanced Topics

Improving query accuracy within the privacy budget

Differential Privacy and Floating Point Accuracy

Floating point math on computer's isn't continuous, and differential privacy implementations that assume it is may experience a variety of errors that result in privacy loss. A discussion of the problems inherently in floating-point arithmetic can be found in Oracle's What Every Computer Scientist Should Know About Floating-Point Arithmetic, an edited reprint of the paper What Every Computer Scientist Should Know About Floating-Point Arithmetic, by David Goldberg, published in the March, 1991 issue of Computing Surveys.

"How Will Statistical Agencies Operate When All Data Are Private?" (MS #1142) has been published to Journal of Privacy and Confidentiality. http://repository.cmu.edu/jpc/vol7/iss3/1

Differential Privacy and the Statistical Agencies


The Fool's Gold Controversy

What's wrong with this article and with the followups?

Other attacks

Math

p for randomized response rate:

$p = \frac{e^\epsilon}{1+e^\epsilon}$

Probability that randomized response should be flipped.

See Also

Online Resources