31–40 of 99 posts
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.
Theoretically speaking if the generated data has the same distribution and parameters as the real data [1], and encodes similar nonparametric features like seasonality and user activity, I think generated data might be fine. [2]
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1. Admittedly tricky if you have limited data and no insight into the underlying population distribution/features, just those of the sample. But then you have a worse problem for modeling diagnostics anyway.
2. In the sense that anything is "fine", which is a spectrum that requires some critical skepticism in statistics. There are always caveats but it may still be robust and useful.
Earlier quoted context omitted.
True, Amnesia can also be run locally!
That's not at all obvious from the marketing pages, possibly a point of improvement? It would be my #1 concern.
Less prominent than the "online version" button though.
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…
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…
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…
Unfortunately, many aspects of the GDPR are interpreted very heterogeneously, both in individual countries and by different supervisory authorities within the countries themselves.
For this reason, it is essential that more specific guidelines and certifications are developed for the use of different technologies, including anonymization.
Use synthetic data instead? https://tonic.ai/
However, this trade-off can be of a different nature, resulting in advantages for synthetization, for example when protecting high-dimensional data.