From 83be6545dae6d37c584e88c67680d4eef22c6df7 Mon Sep 17 00:00:00 2001
From: fria <138676274+friadev@users.noreply.github.com>
Date: Tue, 1 Jul 2025 07:16:28 -0500
Subject: [PATCH] add more info to the problem

---
 blog/posts/differential-privacy.md | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/blog/posts/differential-privacy.md b/blog/posts/differential-privacy.md
index 8e48a540..12d7c972 100644
--- a/blog/posts/differential-privacy.md
+++ b/blog/posts/differential-privacy.md
@@ -19,7 +19,9 @@ Is it possible to collect data from a large group of people but protect each ind
 
 ## 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:
+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.
+
+Latanya Sweeney in a [paper](https://dataprivacylab.org/projects/identifiability/paper1.pdf) from 2000 used U.S. Census data to try and re-identify people solely based on the metrics available to her. She found that 87% of Americans could be identified based on only 3 metrics: ZIP code, date of birth, and sex.
 
 ## History