mirror of
https://github.com/privacyguides/privacyguides.org.git
synced 2025-07-29 17:38:43 -04:00
update(blog)!: Privacy-Enhancing Technologies Series: Differential Privacy
This commit is contained in:
parent
e504efe7e4
commit
a506f32cd0
1 changed files with 26 additions and 0 deletions
26
blog/posts/differential-privacy.md
Normal file
26
blog/posts/differential-privacy.md
Normal file
|
@ -0,0 +1,26 @@
|
|||
---
|
||||
date:
|
||||
created: 2025-07-01T17:30:00Z
|
||||
categories:
|
||||
- Explainers
|
||||
authors:
|
||||
- fria
|
||||
tags:
|
||||
- Privacy Enhancing Technologies
|
||||
- Differential Privacy
|
||||
license: BY-SA
|
||||
schema_type: BackgroundNewsArticle
|
||||
description: |
|
||||
Privacy Pass is a new way to privately authenticate with a service. Let's look at how it could change the way we use services.
|
||||
---
|
||||
# Privacy-Enhancing Technologies Series: Differential Privacy
|
||||
|
||||
Is it possible to collect data from a large group of people but protect each individual's privacy? In this entry of my series on privacy-enhancing technologies, we'll discuss differential privacy and how it can do just that.<!-- more -->
|
||||
|
||||
## Problem
|
||||
|
||||
It's useful to collect data from a large group of people. You can see trends in a population. But it requires a lot of individual people to give up personally identifiable information. Even things that seem inocuous like your gender can help identify you. 87% of Americans can be identified by three pieces of information:
|
||||
|
||||
## History
|
||||
|
||||
Most of the concepts I write about seem to come from the 70's and 80's, but differential privacy is a relatively new concept. It was first introduced in a paper from 2006 called [*Calibrating Noise to Sensitivity in Private Data Analysis*](https://desfontain.es/PDFs/PhD/CalibratingNoiseToSensitivityInPrivateDataAnalysis.pdf)
|
Loading…
Add table
Add a link
Reference in a new issue