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Debunking the Myth of "Anonymous" Data

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Re: Debunking the Myth of "Anonymous" Data

#11

Post by c0pium »

95014_refugee wrote: post #7
Forbo wrote: post #5

Earlier quoted context omitted.

Still sounds potentially problematic. Per wikipedia: "Differential privacy provides a quantified measure of privacy loss and an upper bound and allows curators to choose the explicit trade-off between privacy and accuracy. It is robust to still unknown privacy attacks. However, it encourages greater data sharing, which if done poorly, increases privacy risk. Differential privacy implies that privacy is protected, but…

You are already dependent on a set of curators to not simply outright lie and export the data as captured. This take lacks subtlety; unless you are going to abandon the set of functionality ("where is the best fried chicken near me?") that this sort of metadata facilitates, you need to make decisions about which curators you trust, and then participate in driving them to honesty and accountability. From my perspectiv…

The problem with the EFF is that it’s full of people who made up their minds about what’s ok and what isn’t over a decade ago, and they are largely just playing the hits now. No new material, and no consideration that things might change.

Re: Debunking the Myth of "Anonymous" Data

#12

Post by c0pium »

jdietrich wrote: post #6

GDPR specifically mentions pseudonymous data in Recital 26: "The principles of data protection should apply to any information concerning an identified or identifiable natural person. Personal data which have undergone pseudonymisation, which could be attributed to a natural person by the use of additional information should be considered to be information on an identifiable natural person. To determine whether a nat…

That is almost verbatim the definition of PII from Wikipedia and from OMB Memorandum M-07-1616 (the US government definition of PII).

Re: Debunking the Myth of "Anonymous" Data

#13

Post by spiffytech »

Every time I hear "anonymous data", I think of that time AOL published anonymized search logs (for academic research). The anonymization was negligent, and an NYT reporter de-anonymized and tracked down one of the users with the local & personal info present in the search queries.

https://en.wikipedia.org/wiki/AOL_search_log_release

https://web.archive.org/web/20130404175032/http://www.nytime...

Re: Debunking the Myth of "Anonymous" Data

#14

Post by willseth »

pixl97 wrote: post #4
jruohonen wrote: post #2

A good popular take, but they, either intentionally or out of ignorance, omit newer, proven techniques like differential privacy.

In particular areas things like differential privacy may work, for example medical sets where there are lots of regulations and potential fines for the companies involved. But do you think your average ad tech company gives a fuck? They are going to keep the original data because that's where the money is. Yea, maybe they'll have privacy datasets they sell/release to other groups, but all the real data will remain in…

It's not because of the money. Most could make money just fine with properly anonymized data. They just don't care and/or don't want to take the effort or spend money to do it because the consequences for leaking private info are so minimal.

Re: Debunking the Myth of "Anonymous" Data

#15

Post by JohnFen »

Forbo wrote: post #5
jruohonen wrote: post #2

A good popular take, but they, either intentionally or out of ignorance, omit newer, proven techniques like differential privacy.

Still sounds potentially problematic. Per wikipedia: "Differential privacy provides a quantified measure of privacy loss and an upper bound and allows curators to choose the explicit trade-off between privacy and accuracy. It is robust to still unknown privacy attacks. However, it encourages greater data sharing, which if done poorly, increases privacy risk. Differential privacy implies that privacy is protected, but…

I agree. DP is better than no privacy at all, but it certainly doesn't make me feel comfortable.

Re: Debunking the Myth of "Anonymous" Data

#16

Post by willseth »

I work for a data privacy startup, and this article unfortunately groups all forms of anonymization together. It is specifically criticizing forms of anonymization that only treat direct identifiers like names, addresses, and phone numbers. That is usually referred to as "pseudonymization", and they are correct to point out that an only moderately sophisticated attacker can still link people in the dataset using combinations of indirect identifiers like age, birthday, and zipcode. Pseudonymization is a weak form of privacy.

More sophisticated methods of privacy also anonymize indirect identifiers, and in some cases personal attributes. They do this by adding noise to the data in such a way that the noise has relatively* minimal impact on the results of computations made over the dataset, but a significant impact on the ability to re-identify someone using indirect identifiers or attributes.

*There is always a tradeoff between privacy and utility. The only way to achieve 100% private data is 100% noise, but the privacy-utility tradeoff curve isn't linear, and you can still achieve very good utility and very good privacy in many cases, especially with the best tools. Methods are also improving over time, reducing the impact of the tradeoff.

Re: Debunking the Myth of "Anonymous" Data

#17

Post by JohnFen »

buttercraft wrote: post #3
jruohonen wrote: post #2

A good popular take, but they, either intentionally or out of ignorance, omit newer, proven techniques like differential privacy.

Or they don't want you collecting data in the first place, in which case the techniques are irrelevant.

Entirely this. That data is so widely collected is the root problem.

Re: Debunking the Myth of "Anonymous" Data

#18

Post by willseth »

euniceee3 wrote: post #9

Great article putting all the relevant content in one place. Does anyone know of any de-anonymization services? The startup I am working at is privacy focused and we are looking for a way to demonstrate why you need an additional layer to protect and compartmentalize. Short of us buying up data in bulk and then doing the de-anonymization in-house I am not seeing an easy way to do this. Or even an advertised partner,…

There are a small handful of us out there, targeting slightly different but overlapping use cases, but this is me https://www.privacydynamics.io. Happy to answer any questions about it.

Re: Debunking the Myth of "Anonymous" Data

#19

Post by bertil »

euniceee3 wrote: post #9

Great article putting all the relevant content in one place. Does anyone know of any de-anonymization services? The startup I am working at is privacy focused and we are looking for a way to demonstrate why you need an additional layer to protect and compartmentalize. Short of us buying up data in bulk and then doing the de-anonymization in-house I am not seeing an easy way to do this. Or even an advertised partner,…

This is the same problem as white-hat security: you need people who know an awful lot about how bad guys work but are good guys. Security has developed a legitimate market over the years, but that took time.

You could try to ask independent consultant(s) who you trust to work on that problem and let them grow that practice. The problem is that they would need to have access to marketing platforms.

Re: Debunking the Myth of "Anonymous" Data

#20

Post by oezi »

jdietrich wrote: post #6

GDPR specifically mentions pseudonymous data in Recital 26: "The principles of data protection should apply to any information concerning an identified or identifiable natural person. Personal data which have undergone pseudonymisation, which could be attributed to a natural person by the use of additional information should be considered to be information on an identifiable natural person. To determine whether a nat…

The crucial piece is your link is:

> 4To ascertain whether means are reasonably likely to be used to identify the natural person, account should be taken of all objective factors, such as the costs of and the amount of time required for identification, taking into consideration the available technology at the time of the processing and technological developments.

This has been interpreted that any objectively possible way to de-anonymize is reasonable. In particular, considering that all the data of the organization doing the anonymization can be used to try to de-anonymize.

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