In my previous post, Differential Privacy: The Basics, I provided an introduction to differential privacy by exploring its definition and discussing its relevance in the broader context of public data release. In this post, I shall demonstrate how easily privacy can be breached and then counter this by showing how differential privacy can protect against this attack. I will also present a few other examples of differentially private queries.
There has been a lot of online comment recently about a dataset released by the New York City Taxi and Limousine Commission. It contains details about every taxi ride (yellow cabs) in New York in 2013, including the pickup and drop off times, locations, fare and tip amounts, as well as anonymized (hashed) versions of the taxi’s license and medallion numbers. It was obtained via a FOIL (Freedom of Information Law) request earlier this year and has been making waves in the…
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