- From: Taylor Kendal <taylor@learningeconomy.io>
- Date: Tue, 30 Jun 2020 15:48:50 +0000
- To: "daniel.hardman@evernym.com" <daniel.hardman@evernym.com>, Kim Hamilton <kimdhamilton@gmail.com>
- CC: Liam McCarty <liam@unumid.org>, Credentials Community Group <public-credentials@w3.org>
- Message-ID: <CY4PR1301MB2072B64D5D2E66C58D0DAC1DAA6F0@CY4PR1301MB2072.namprd13.prod.outlook.>
Yes, thank you Liam! NCSL also held a webinar on this topic a few months ago - https://youtu.be/PAqE27VcWvs; what the Census calls disclosure avoidance<https://www.census.gov/about/policies/privacy/statistical_safeguards.html>. 3Blue1Brown<https://www.youtube.com/channel/UCYO_jab_esuFRV4b17AJtAw> offers great content similar to Minute Physics—yay, free education! Great related deconstruction of contact tracing here: https://youtu.be/D__UaR5MQao Taylor Kendal www.learningeconomy.io<http://www.learningeconomy.io> ________________________________ From: Daniel Hardman <daniel.hardman@evernym.com> Sent: Tuesday, June 30, 2020 8:59 AM To: Kim Hamilton Cc: Liam McCarty; Credentials Community Group Subject: Re: Differential privacy in the Census (MinutePhysics video) I wanted to endorse this video as well. Very interesting. One application in the VC space (perhaps there are others, but this one occurs to me) might be to monitor which fields are selectively disclosed to a specific verifier (in one or multiple proving interactions), and apply the mathematics to know how close the holder is getting to being strongly identified. I was familiar with this idea already, but unaware that there were formally proven mathematics to measure it. Cool stuff! On Mon, Jun 29, 2020 at 6:37 PM Kim Hamilton <kimdhamilton@gmail.com<mailto:kimdhamilton@gmail.com>> wrote: Thanks for sharing this Liam. I'm very interested in mathematical/formal approaches to privacy guarantees. Any such content will be eagerly absorbed! Thanks again! Kim On Fri, Jun 12, 2020 at 12:54 PM Liam McCarty <liam@unumid.org<mailto:liam@unumid.org>> wrote: A great video on differential privacy in U.S. Census statistics (made by MinutePhysics): https://www.youtube.com/watch?v=pT19VwBAqKA. 2020 is the first year the Census can guarantee mathematically robust privacy! This is from way back in September, but thought this would be of interest to the community. Liam Liam McCarty Co-Founder of Unum ID<http://www.UnumID.org>
Received on Tuesday, 30 June 2020 15:49:12 UTC