However it’s also true that of you don’t do it correctly users can be identified. Sounds like Netflix didn’t do it properly. I don’t know, do you have a link I could look at?
Create anonymous UUID, store interactions against this in a separate table, ensure PII is removed prior to storing. So instead of Max Reboo has purchased a subscription to jugs and hooters it’s user 12345678901234576 has purchased jugs and hooters. How can a future treadmill de-anonymise this? For sure if the storage is done badly then you can track back to a particular user.
Also, once again, can you link to the netflix issue you quoted above please. Thanks.
you can’t “anonymize” data
ask the people outed as lgbt by netflix’s anonymized data set
You absolutely can anonymise data.
However it’s also true that of you don’t do it correctly users can be identified. Sounds like Netflix didn’t do it properly. I don’t know, do you have a link I could look at?
anonymising data is a treadmill problem
what might work now won’t hold up to the de-anonymising techniques of a few years from now
so no, you can’t really
Create anonymous UUID, store interactions against this in a separate table, ensure PII is removed prior to storing. So instead of Max Reboo has purchased a subscription to jugs and hooters it’s user 12345678901234576 has purchased jugs and hooters. How can a future treadmill de-anonymise this? For sure if the storage is done badly then you can track back to a particular user.
Also, once again, can you link to the netflix issue you quoted above please. Thanks.
which is more or less exactly what netflix did -> the whole thing’s not that hard to find on google
but you need something to distinguish users at least a bit or the data’s equivalent to sales figures
you combine that “not-quite-pii” with other independent data sources that have similar “not-quite-pii” and build a complete picture
the treadmill effect comes from active research in this exact area trying to de-anonymise data sets finding new techniques to get around old ones