3 ms·

> I know it will never be hundred percent leak proof A slow leaking ship will still sink. Attempts so far to anonymise public datasets have been terrible and t

> I know it will never be hundred percent leak proof A slow leaking ship will still sink. Attempts so far to anonymise public datasets have been terrible and turned into a garbage fire by attackers every time with minimal effort. Don't hand out false promises. Guess you are looking for fully homomorphic encryption. A long-outstanding problem with lots of smart people working on it, some are doing ok at getting there. https://github.com/ibm/fhe-toolkit-linux https://github.com/ibm/fhe-toolkit-linux

michealr 6y ago
Thats true, a poorly chosen description on my part. Very cool, had read about homomorphic systems. For fully homomorphic systems has there been successful SAAS like offering allowing use of such a systems? Or do you think its still in the research oriented phase?
- maest 6y ago
  Not really SaaS, and debatable whether it's successful, but I hear numerai uses homomorphic encryption when providing data for quants to backtest. https://numer.ai/ https://numer.ai/ https://en.wikipedia.org/wiki/Numerai https://en.wikipedia.org/wiki/Numerai EDIT: added qualifier, since i do not know for sure if numerai is using homomorphic encryption.
  - jl2718 6y ago
    It’s not what you’d traditionally call a homomorphic crypto system, but it’s more than just anonymization or privacy preservation. You might call it a ‘homomorphic’ data projection, e.g. matrix multiplication, but I don’t know the details. Technically, I’m not sure it fits the definition of a cryptographic system, because encrypted data is defined as indistinguishable from noise, but obviously the data scientists must find information within it. (There may be something going on that I can’t imagine at the moment.)
- kasperni 6y ago
  Definitely still in the research phase for what you are looking for. Performance is anywhere from 5-15 magnitudes slower than ordinary computations. Yes, magnitudes...
cipherboy 6y ago
I'm a little rusty but I swear I saw a partial homomorphic encryption scheme for aggregates and analytics. I want to say Enigma conference, '16 or '17? Maybe by Boston University. The benefit being that while you can run any computatio with a FHE, PHEs are generally faster. IIRC Microsoft was also doing research on PHEs.
- michealr 6y ago
  Interesting, did Microsoft bring the research any further?
  - cipherboy 6y ago
    https://dl.acm.org/doi/abs/10.1145/2463676.2467797 https://dl.acm.org/doi/abs/10.1145/2463676.2467797 Might be what I was thinking of. I'm sure you can find other publications as well. I'm no longer at University and I've lost touch with that professor so I'm not sure their current research.
dataewan 6y ago
Differential privacy is an area that makes some guarantees about not letting personal information about individuals escape. Might be a useful technique as well. https://en.wikipedia.org/wiki/Differential_privacy https://en.wikipedia.org/wiki/Differential_privacy Agree that strong guarantees about privacy aren't achievable.
- rapnie 6y ago
  Yes, I found this the other day: https://smartnoise.org/ https://smartnoise.org/ Need to read more about the concept. Anyone with more good resources?

michealr 6y ago

Thats true, a poorly chosen description on my part. Very cool, had read about homomorphic systems. For fully homomorphic systems has there been successful SAAS like offering allowing use of such a systems? Or do you think its still in the research oriented phase?

maest 6y ago
Not really SaaS, and debatable whether it's successful, but I hear numerai uses homomorphic encryption when providing data for quants to backtest. https://numer.ai/ https://numer.ai/ https://en.wikipedia.org/wiki/Numerai https://en.wikipedia.org/wiki/Numerai EDIT: added qualifier, since i do not know for sure if numerai is using homomorphic encryption.
- jl2718 6y ago
  It’s not what you’d traditionally call a homomorphic crypto system, but it’s more than just anonymization or privacy preservation. You might call it a ‘homomorphic’ data projection, e.g. matrix multiplication, but I don’t know the details. Technically, I’m not sure it fits the definition of a cryptographic system, because encrypted data is defined as indistinguishable from noise, but obviously the data scientists must find information within it. (There may be something going on that I can’t imagine at the moment.)
kasperni 6y ago
Definitely still in the research phase for what you are looking for. Performance is anywhere from 5-15 magnitudes slower than ordinary computations. Yes, magnitudes...

cipherboy 6y ago

I'm a little rusty but I swear I saw a partial homomorphic encryption scheme for aggregates and analytics. I want to say Enigma conference, '16 or '17? Maybe by Boston University. The benefit being that while you can run any computatio with a FHE, PHEs are generally faster. IIRC Microsoft was also doing research on PHEs.

michealr 6y ago
Interesting, did Microsoft bring the research any further?
- cipherboy 6y ago
  https://dl.acm.org/doi/abs/10.1145/2463676.2467797 https://dl.acm.org/doi/abs/10.1145/2463676.2467797 Might be what I was thinking of. I'm sure you can find other publications as well. I'm no longer at University and I've lost touch with that professor so I'm not sure their current research.

dataewan 6y ago

Differential privacy is an area that makes some guarantees about not letting personal information about individuals escape. Might be a useful technique as well. https://en.wikipedia.org/wiki/Differential_privacy https://en.wikipedia.org/wiki/Differential_privacy Agree that strong guarantees about privacy aren't achievable.

rapnie 6y ago
Yes, I found this the other day: https://smartnoise.org/ https://smartnoise.org/ Need to read more about the concept. Anyone with more good resources?