A webcomic explainer on how the census deals with digital privacy

Journalist's Resource published this great comic by Josh Neufeld, explaining the basic concepts behind differential privacy, the data collection method used to prevent bad actors from de-anonymizing the information gleaned from the 2020 Census.

The original source includes some other great resources on differential privacy, but since the comic itself is made available under a Creative Commons Attribution-NoDerivatives 4.0 International License, we've re-posted it here in full.

 

A brief introduction to differential privacy: A data protection plan for the 2020 census [Josh Neufeld / Journalist's Resource] Read the rest

Google releases a free/open differential privacy library

"Differential privacy" (previously) is a promising, complicated statistical method for analyzing data while preventing reidentification attacks that de-anonymize people in aggregated data-sets. Read the rest

Apple's fine-print reveals a secret program to spy on Iphone users and generate "trust scores"

Buried in the new Apple Iphone and Apple TV privacy policy is an unannounced program that uses "information about how you use your device, including the approximate number of phone calls or emails you send and receive...to compute a device trust score when you attempt a purchase." Read the rest

An incredibly important paper on whether data can ever be "anonymized" and how we should handle release of large data-sets

Even the most stringent privacy rules have massive loopholes: they all allow for free distribution of "de-identified" or "anonymized" data that is deemed to be harmless because it has been subjected to some process. Read the rest