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New for: D1, D2, D3, INET, D4, D5, D6

What and Who

Most data anonymity attack papers are inconclusive or misleading

Paul Francis
MMCI
Joint Lecture Series
AG 1, AG 2, AG 3, INET, AG 4, AG 5, D6, SWS, RG1, MMCI  
Public Audience
English

Date, Time and Location

Wednesday, 3 November 2021
12:15
60 Minutes
Virtual talk
Virtual
Saarbrücken

Abstract

There are dozens or perhaps hundreds of papers that claim that some data release that was thought to protect privacy does not. This has led to a widespread belief that anonymized data is easily attacked. As a result, organizations may stop releasing certain valuable data (Netflix recommendations, certain statistics on genetic studies), or apply strong anonymization that reduces the utility of the data (US Census Bureau, Facebook URLs dataset). In this broadly accessible talk, I will argue that most data anonymity attack papers don't measure privacy correctly, leading to conclusions that are at best invalid, and often very misleading. I will describe a more appropriate measure that we have used in the past in our anonymity bounty program. This is work in progress.

Contact

Jennifer Müller
+49 681 9325 2900
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Virtual Meeting Details

Zoom
997 1565 5535
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Jennifer Müller, 11/25/2021 11:25
Jennifer Müller, 10/18/2021 12:01 -- Created document.