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Amnesia – High-Accuracy Data Anonymization

amnesia.openaire.eu

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Re: Amnesia – High-Accuracy Data Anonymization

#14
For data to be anonymous under GDPR, it is not enough that individuals cannot be identified from the anonymized data set. If individuals can be identified when the anonymous data set is compared with the source data set, the anonymized data is not "anonymous".

For data to be truly anonymous under GDPR. there must be no other additional data that would allow for reidentification. If there is any other data that, when combined with the anonymous data, allows for reidentification, the data set is only pseudonymous and must be treated as personal data under GDPR.

Re: Amnesia – High-Accuracy Data Anonymization

#15

For data to be anonymous under GDPR, it is not enough that individuals cannot be identified from the anonymized data set. If individuals can be identified when the anonymous data set is compared with the source data set, the anonymized data is not "anonymous". For data to be truly anonymous under GDPR. there must be no other additional data that would allow for reidentification. If there is any other data that, when…

That's the most concise and clear formulation of that I've seen so far. Thanks.

Re: Amnesia – High-Accuracy Data Anonymization

#17
post #5

Fair warning: anonymization is a hard problem. It is never easy, and you'd be surprised how many bits can leak out of what you thought was properly anonymized data. If you are using data for test purposes please use generated data, not anonymized data. This has the additional advantage that there is no potential path for live data to end up on a developers machine. added in edit: And also realize that just using a se…

What about building machine learning models that make predictions on said data? Can't just test on fake data.

Re: Amnesia – High-Accuracy Data Anonymization

#18
post #5

Fair warning: anonymization is a hard problem. It is never easy, and you'd be surprised how many bits can leak out of what you thought was properly anonymized data. If you are using data for test purposes please use generated data, not anonymized data. This has the additional advantage that there is no potential path for live data to end up on a developers machine. added in edit: And also realize that just using a se…

What about building machine learning models that make predictions on said data? Can't just test on fake data.

There is a German company that specializes in this: https://www.statice.ai/ , and that too is a path that you should only walk if you fully understand the subject matter.

So you could instead test on fake data that has the same (or as much as possible the same) statistical properties as the data that you would like to use.

Re: Amnesia – High-Accuracy Data Anonymization

#20
post #19
post #12

Earlier quoted context omitted.

There are plenty of valid reasons to share data, e.g. for medical research among others.

Then get informed consent

That's a must. In some countries this is now automated at the government level, Belgium for instance has an excellent consent mechanism for medical data.
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