71–80 of 107 posts
Figuring out which of those traces belonged to which employee was a real puzzle /s
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 comb…
> However, in practice, any attempt at de-identification requires removal not only of your identifiable information, but also of information that can identify you when considered in combination with other information known about you.
So, anonymization may be well intended and sophisticated, but is only effective as long as you control and anonymize all the data available to your adversary. Which you obviously cannot. The best you can achieve with anonymized data is to allow non-malicious users to run some analysis on your data in a controlled environment without exposing them to information they should not see. If that's your employer's business model, well, there may be a market niche for that.
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,…
Earlier quoted context omitted.
I'm usually the first to defend the EFF but I agree that they've gone a bit far here. The anonymization script which I wrote for my company just replaces every string in the customer's database with a cryptographic hash--except a list of strings like "failed" and "success". So unless your city is named "success", it's going to be missing from the dataset. It's a bit bewildering to actually run the app in this mode, b…
> replaces every string in the customer's database with a cryptographic hash > So unless your city is named "success", it's going to be missing from the dataset. You've made the typical mistake of thinking that just because you've made it harder , you've also made it anonymous. For instance, you might have replaced "Chicago" with 9cfa1e69f507d007a516eb3e9f5074e2, but if for instance a lot of people with that tokenise…
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 comb…
In the interest of charitable-ness, can you define "noise" and explain how rudimentary denoising algorithms that have existed since the 1960s can't penetrate it? Time and time again people think they've anonymized data and they're always proven incorrect. Just come to grips with the fact you're participating in the sale of my (or whoever's) private data. Hope you sleep well!
This is pretty obvious survivorship bias. You think that they’re wrong because you only hear about the cases when they were. There are tons of examples of breaches where the anonymization held up, it’s just that it’s not interesting so nobody talks about it.
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Another fun one was the Netflix Prize, where Netflix published an anonymized dataset, but some researchers at UT Austin were able to de-identify many/most of the users in the dataset by linking them to IMDB profiles based on preferences.
There's no way most of the users in the Netflix data had IMDb accounts.
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 possibl…
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 comb…
The original datasets are brokered anyway. [citations disclosed]
Earlier quoted context omitted.
Another fun one was the Netflix Prize, where Netflix published an anonymized dataset, but some researchers at UT Austin were able to de-identify many/most of the users in the dataset by linking them to IMDB profiles based on preferences.
There's no way most of the users in the Netflix data had IMDb accounts.
many I would have been fine with. most? no way.