
Differential privacy for dummies - mrry
https://github.com/frankmcsherry/blog/blob/master/posts/2016-02-03.md
======
iampims
To anyone interested by differential privacy I would recommend this article:
[http://research.neustar.biz/2014/09/08/differential-
privacy-...](http://research.neustar.biz/2014/09/08/differential-privacy-the-
basics/)

It does a very good job of explaining the basics.

They also published a follow up with the quite popular taxi dataset:
[http://research.neustar.biz/2014/09/15/riding-with-the-
stars...](http://research.neustar.biz/2014/09/15/riding-with-the-stars-
passenger-privacy-in-the-nyc-taxicab-dataset/)

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amelius
> The formal version of differential privacy requires that the probability a
> computation produces any given output changes by at most a multiplicative
> factor when you add or remove one record from the input.

What is the significance of this? This statement means nothing. The context
should be better described. I thought this was a "for dummies" article.

~~~
danbruc
I also turned to Wikipedia immediately. Differential privacy is concerned with
protecting individual records when making statistical queries. For example, if
you could issue a query to a medical case database like »What proportion of
the population was born on this specific date in that specific small town with
some specific eye color and has this illness?« you could potentially figure
out whether or not one person has a specific illness by either getting zero or
a very small percentage. One possible solution and what is mostly discussed in
the article is adding some noise to the result, as little as possible to not
make the query result meaningless but enough to protect each record.

