News for hackers. Stuff that matters.
Re:Differential privacy tools from MS Research and Harvard by Sephr on Saturday July 04, 2020 @05:31AM (#23731206)
From https://github.com/opendifferentialprivacy/whitenoise-core:

"Differential privacy is the gold standard definition of privacy protection."

Differential privacy is nice, but it's still tracking and "less tracking" is absolutely not the gold standard definition of privacy protection. That title goes to "no tracking"

Re:Differential privacy tools from MS Research and Harvard by frankmcsherry on Saturday July 04, 2020 @09:08AM (#23731984)
> That title goes to "no tracking"

This is roughly analogous to "abstinence is the best form of birth control". It's not wrong, but it also isn't particularly realistic or helpful. The reality is that people often do want to exchange data, some times because it is legally or morally mandated, and tools that allow this to be done as safely as possible are important.

If you have free cycles, you can read more here:

https://github.com/frankmcsherry/blog/blob/master/posts/2017...

Re:Differential privacy tools from MS Research and Harvard by Sephr on Saturday July 04, 2020 @11:21AM (#23732843)
I'm all for these tools being published and used where appropriate. I'm only criticizing their description as the "gold standard for privacy protection" which seems disingenuous.
Re:Differential privacy tools from MS Research and Harvard by legulere on Monday July 06, 2020 @02:18AM (#23745193)
Sex is a human need. Tracking people isn’t. Collecting data on people is rarely done because of a legal or moral reason. And for those cases (like medical studies) pseudonymisation and anonymisation already works well.
Re:Differential privacy tools from MS Research and Harvard by im3w1l-alt on Saturday July 04, 2020 @04:43PM (#23734796)
Abstinence only is an interesting meme. It's successful as a meme precisely because the advice does not work.
Re:Differential privacy tools from MS Research and Harvard by currymj on Saturday July 04, 2020 @09:53AM (#23732169)
the focus of the project seems not to be on differential privacy as used by private companies but by scientists. in many cases you can't (US Census, medical records) or wouldn't want to (public health research) stop collecting the data. and allowing privacy-preserving statistical queries from outside researchers has the potential to be very useful.
Re:Differential privacy tools from MS Research and Harvard by Sephr on Saturday July 04, 2020 @11:26AM (#23732886)
> allowing privacy-preserving statistical queries from outside researchers has the potential to be very useful

This depends on how many researchers and queries per researcher that you want to allow. The privacy budget eventually runs out, so there are definitely drawbacks that prevent effective use of this data across enough outside researchers.

Re:Differential privacy tools from MS Research and Harvard by mjohn on Saturday July 04, 2020 @06:01AM (#23731308)
Privacy is not just relevant to advertising. There are a huge number of research opportunities in the social sciences that could benefit and can help make the world better.
Re:Differential privacy tools from MS Research and Harvard by m463 on Saturday July 04, 2020 @08:38AM (#23731841)
Here's the fallacy: people think if they collect ALL the data, they will have the best results with whatever problem they're trying to solve.

Right now you're probably wondering, yeah, but there's this one problem that wouldn't have been solved if x or y....

But really it's just hoarding behavior. They're trying to collect it all. Statistical significance is reached very quickly and after that point they're doing harm to society.

Re:Differential privacy tools from MS Research and Harvard by kohtatsu on Saturday July 04, 2020 @06:48AM (#23731449)
Show me what data you've collected and would like to share, including metadata, and if you ask nicely then most of the time I'd be more than happy to share it.

Things like emoji usage, page navigations, feature uses, etc. Ideally anonymous; no IP, user agent, etc, just a small byte or two packed properly can go a long way.

Re:Differential privacy tools from MS Research and Harvard by ghaff on Saturday July 04, 2020 @08:02AM (#23731719)
>Ideally anonymous

The problem is that it's actually quite hard to reliably anonymize data especially once you start to begin combining data sets from multiple places. That's the problem differential privacy is trying to solve in a mathematically rigorous way.

See for example how researchers partially de-anonymized Netflix Prize data by cross-referencing it with IMDB reviews.

Re:Differential privacy tools from MS Research and Harvard by zzzcpan on Saturday July 04, 2020 @09:55AM (#23732182)
It's not possible to reliably anonymize data and still be able to infer something from it, the idea is just too logically broken. Because the whole reason for anonymity is to make sure no information about any individual or a set of individuals of the size decided by those seeking such protection can be inferred from the data by the parties that want to infer something from it. While "differential privacy" assumes that not being able to infer information about relatively small sized sets of individuals decided by the parties who want to infer something from the data is "privacy". It isn't of course, it's a pretty dystopian use of the word privacy. Hence why corporations love this stuff, privacy without privacy is godsent to them.
Re:Differential privacy tools from MS Research and Harvard by kohtatsu on Saturday July 04, 2020 @11:37AM (#23732972)
Depends on the data.

DDG:

  { used_advanced_search }
  { used_country_toggle }
  { tabbed, *tab_maps }
  { filtered, *filter_date }
  { os "iOS", *ver "13.5", browser "Safari" }
iOS:

  Mail
  { disabled_remote_images }
  { flagged_mail }
  
  Keyboard
  { emoji_keyboard_via_globe }
  { *emoji_use "100-1000", *emojis [ ":)" ":P" ":(" ] }

Each of these could be stored separately without metadata then aggregated no problem. Things marked * could be left out, and some things could be randomized up or down buckets and such.
Re:Differential privacy tools from MS Research and Harvard by im3w1l on Saturday July 04, 2020 @05:06PM (#23734913)
Social scientists are hateful hateful people. They say they are like physicists but they are more similar to prosecutors.

"Everything you say can and will be used against you"

All they study is ways you are bad, and all they research is ways to keep you down.

If anyone reaches the wrong conclusion "maybe they are innocent.." Then it only takes two seconds, then they are fired.

Privacy from social scientists is one of the most important forms of privacy.