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Amnesia – High-Accuracy Data Anonymization

amnesia.openaire.eu

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Re: Amnesia – High-Accuracy Data Anonymization

#91

Post by freshhawk »

braincoke wrote: post #28
simongray wrote: post #25

Earlier quoted context omitted.

Amnesia doesn't...? Then what's the download link and github page for?

The Readme is not user friendly and doesn't explain how to use or install the software. In the Github issue the developer points to an installation documentation that throws a 404 error. In my opinion, this source code was put out to appear "open" to the H2020 Programme, but they have no intention in actually helping users run the code locally.

Yeah, wow. This is one of the more aggressive examples of "open"-but-unrunnable I've ever seen. I think your opinion is dead on.

And if this isn't intentional, then the level of effort is so low how could you trust the software with such a complex and subtle problem? It is clearly intentional, but they didn't even give themselves a plausibly deniable story.

Re: Amnesia – High-Accuracy Data Anonymization

#93

Post by jimktrains2 »

lelandbatey wrote: post #81
Aerroon wrote: post #79

Earlier quoted context omitted.

Earlier this year we saw articles published about the finding of an Earth-sized rogue planet in our galaxy. The way it was discovered is remarkable. A telescope was looking at a distant star, then the star seemingly brightened over a period of 42 minutes. And that was basically it. When a massive object passes between a distant star and an Earth-based observer the light coming from the star gets deflected and focused…

Indeed, the ability to very accurately infer lots from very small amount of data is something I've long though of as the "Sherlock Holmes" problem. If there's just a few people with the ability to deduce lots of things, then they can be amusing and offer some limited utility, like Sherlock Holmes. Computers are powerful enough though, and people clever enough, that everyone can now have a Sherlock Holmes in their poc…

I think it's the same problem as surveillance. When tailing someone required a substantial investment of an actual person's time and a wiretap literally required physical handling of the physical lines to that person's phone, it makes/made sense to give the police wide leverage in who they put under a lens because it required a substantial investment of time from the police in a way that was intrinsically limited and unable to scale to the population level.

Enter today, when nearly everyone can be and is surveiled with detail cops of previous generation could only dream of, and we're still dealing with those same laws, but we removed the unwritten premises that they're based on: surveillance couldn't scale.

Re: Amnesia – High-Accuracy Data Anonymization

#94

Post by [deleted] »

Geminidog wrote: post #90
Toutouxc wrote: post #85

Earlier quoted context omitted.

I'm a grown up man with a shoe size of 40 (8). Is the 2018 movie Smallfoot insensitive towards me? I mean, I don't enjoy hearing about your suffering and I certainly don't wish it upon you, but why would you care about the name? Do you think that people somehow treat amnesia sufferers with less respect when they're exposed to the name in a context that's not explicitly serious and negative?

The same logic can be applied to black people and the n-word. Shall I name a product after the n-word with no harm intended or being explicitly serious or negative? Does that make it right? No. You may not be offended by the word "smallfoot" but that's just you. You can't make that judgment for black people and the n-word anymore then you can make that judgment for the word "amnesia" and the entire community of amnes…

[deleted]

Re: Amnesia – High-Accuracy Data Anonymization

#95

Post by Mary-Jane »

Spivak wrote: post #78
Mary-Jane wrote: post #41

Earlier quoted context omitted.

Can someone explain the point of this requirement? If a malicious actor has access to the source data there's no need to compare it to anonymized data. What am I missing?

It's an easy-to-state largely foolproof test to see if data really is anonymized. The thing that you're worried about with poorly-anonymized datasets is that if you have another non-anonymized dataset you can combine them to deduce the original information. "Your data set must not be able to be combined with any others that would allow them to infer the original data" is hard. How could you possibly test them all? We…

Let's say you're doing a study of fingerprint patterns. You anonymize a collection of fingerprints from a non-anonymized source by stripping everything but the fingerprint images. Because fingerprints are unique it seems like it'd be impossible to meet the GDPR criteria; even if the only thing that was left was the fingerprints, when compared against the source dataset they will be identified. a) is this interpretation accurate? b) if so, it seems that there's large swaths of data that can never be in compliance. What are the implications for medical research, for instance?

Re: Amnesia – High-Accuracy Data Anonymization

#96

Post by tingletech »

ska wrote: post #83
tingletech wrote: post #76

Earlier quoted context omitted.

How are you going to do COVID-19 research with generated test data?

jacquesm was talking about test purposes, which is a different problem.

sure, but I don't think that is the use case for this tool

Re: Amnesia – High-Accuracy Data Anonymization

#97

Post by Spivak »

Mary-Jane wrote: post #95
Spivak wrote: post #78

Earlier quoted context omitted.

It's an easy-to-state largely foolproof test to see if data really is anonymized. The thing that you're worried about with poorly-anonymized datasets is that if you have another non-anonymized dataset you can combine them to deduce the original information. "Your data set must not be able to be combined with any others that would allow them to infer the original data" is hard. How could you possibly test them all? We…

Let's say you're doing a study of fingerprint patterns. You anonymize a collection of fingerprints from a non-anonymized source by stripping everything but the fingerprint images. Because fingerprints are unique it seems like it'd be impossible to meet the GDPR criteria; even if the only thing that was left was the fingerprints, when compared against the source dataset they will be identified. a) is this interpretati…

I think you nailed it that some data can’t really be anonymized. How could you anonymize emails, names, social security numbers, DNA samples?

You don’t have to use anonymized data all the time, it’s just that the requirements for handling and passing around such data is lower.

Re: Amnesia – High-Accuracy Data Anonymization

#98

Post by Mary-Jane »

Spivak wrote: post #97
Mary-Jane wrote: post #95

Earlier quoted context omitted.

Let's say you're doing a study of fingerprint patterns. You anonymize a collection of fingerprints from a non-anonymized source by stripping everything but the fingerprint images. Because fingerprints are unique it seems like it'd be impossible to meet the GDPR criteria; even if the only thing that was left was the fingerprints, when compared against the source dataset they will be identified. a) is this interpretati…

I think you nailed it that some data can’t really be anonymized. How could you anonymize emails, names, social security numbers, DNA samples? You don’t have to use anonymized data all the time, it’s just that the requirements for handling and passing around such data is lower.

I don't understand the point though; if someone has the source data, what good is the anonymized data to them? What value is added by requiring more stringent safeguards on data that can't be anonymized this way?

Re: Amnesia – High-Accuracy Data Anonymization

#99

Post by Mary-Jane »

warkdarrior wrote: post #68
MaxBarraclough wrote: post #48

Earlier quoted context omitted.

> The source dataset lets those inferences or joins be tied back to the original identifying data. But if the attacker lacks the source dataset, they can't do this, and if they possess the source dataset, they'd use it for their analysis rather than using the anonymised dataset.

The point is that if the attacker can connect your user record in the source data with user # 188da24a7789d in the "anonymized" data, they can use that de-identify all information derived or built on the "anonymized" data. Oh, there is Netflix account for user # 188da24a7789d and the IRS released tax summaries for user # 188da24a7789d? That's interesting, since I know that user # 188da24a7789d is really MaxBarracloug…

If a dataset removes all information except for, say, a user's fingerprints, meaning the only information stored in the anonymous dataset is an image of a fingerprint. The nature of fingerprints prevents them from meeting this requirement, as stated, which effectively eliminates any research that can be done with the data. Given that the only way the dataset could be linked to the original user is if an attacker already had access to the source data, how is this regulation benefiting anyone?
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