One More Time With Feeling: 'Anonymized' User Data Not Really Anonymous

["Dave Farber" <dave () farber net>]

---------- Forwarded message ---------
From: Dewayne Hendricks <dewayne () warpspeed com>
Date: Fri, Jan 27, 2017 at 1:45 AM
Subject: [Dewayne-Net] One More Time With Feeling: 'Anonymized' User Data
Not Really Anonymous
To: Multiple recipients of Dewayne-Net <dewayne-net () warpspeed com>


[Note:  This item comes from friend David Rosenthal.  DLH]

One More Time With Feeling: 'Anonymized' User Data Not Really Anonymous
from the we-can-see-you dept
By Karl Bode
Jan 26 2017
<
https://www.techdirt.com/articles/20170123/08125136548/one-more-time-with-feeling-anonymized-user-data-not-really-anonymous.shtml
>

As companies and governments increasingly hoover up our personal data, a
common refrain to keep people from worrying is the claim that nothing can
go wrong -- because the data itself is "anonymized" -- or stripped of
personal detail. But time and time again, we've noted how this really is
cold comfort; given it takes only a little effort to pretty quickly
identify a person based on access to other data sets. As cellular carriers
in particular begin to collect every shred of browsing and location data,
identifying "anonymized" data using just a little additional context has
become arguably trivial.

Researchers from Stanford and Princeton universities plan to make this
point once again via a new study being presented at the World Wide Web
Conference in Perth, Australia this upcoming April. According to this new
study, browsing habits can be easily linked to social media profiles to
quickly identify users. In fact, using data from roughly 400 volunteers,
the researchers found that they could identify the person behind an
"anonymized" data set 70% of the time just by comparing their browsing data
to their social media activity:

"The programs were able to find patterns among the different groups of data
and use those patterns to identify users. The researchers note that the
method is not perfect, and it requires a social media feed that includes a
number of links to outside sites. However, they said that "given a history
with 30 links originating from Twitter, we can deduce the corresponding
Twitter profile more than 50 percent of the time."

The researchers had even greater success in an experiment they ran
involving 374 volunteers who submitted web browsing information. The
researchers were able to identify more than 70 percent of those users by
comparing their web browsing data to hundreds of millions of public social
media feeds.

Of course, with the sophistication of online tracking and behavior ad
technology, this shouldn't be particularly surprising. Numerous researchers
likewise have noted it's relatively simple to build systems that identify
users with just a little additional context. That, of course, raises
questions about how much protection "anonymizing" data actually has in both
business practice, and should this data be hacked and released in the wild:

"Yves-Alexandre de Montjoye, an assistant professor at Imperial College
London, said the research shows how "easy it is to build a full-scale
'de-anonymizationer' that needs nothing more than what's available to
anyone who knows how to code." "All the evidence we have seen piling up
over the years showing the strong limits of data anonymization, including
this study, really emphasizes the need to rethink our approach to privacy
and data protection in the age of big data," said de Montjoye.

[snip]

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