[proofofstake]

They switched from structure-preserving encryption to neural encryption (using a neural net's layer activations).

> Just a few months ago this package was released by Louis Aslett at Oxford http://www.louisaslett.com/HomomorphicEncryption/. Louis helped me use his package to do Fan and Vercauteren homomorphic encryption on my dataset. Because the ciphertexts are polynomials it's not too easy for an average data scientist to use the data. That's why I came up with more chill ways of encrypting Numerai's data that the article mentions like order-preserving encryption. There's a security vs easy of use trade off, for sure. But homomorphic encryption is a real thing.

https://www.reddit.com/r/MachineLearning/comments/3zvuge/enc...

Louis Aslett authored https://arxiv.org/abs/1508.06574

[lkowalcz]

Thanks for that link! I was never able to find any details from someone who works for Numerai (or claims to at least)

I still don't think it's fair to market their method as comparable to Aslett's scheme or "standard" notions of homormorphic/order preserving encryption, no matter how "chill" they are :)

[proofofstake]

Do you think neural encryption is closer to encryption? GAN-style: One network encrypts while preserving structure, another network tries to reverse engineer to the original features.

Edit: No specific sources for what Numerai is using, but in general: https://arxiv.org/abs/1610.06918 "Learning to Protect Communications with Adversarial Neural Cryptography".

Edit2: Yes, in general. I would say "yes, this is a valid form of encryption". But I do agree that their marketing was perhaps a bit too optimistic. I have no problem calling it "obfuscation" either (I just think their method of "obfuscation" is way more advanced than removing headers and normalizing within 0-1).

[lkowalcz]

I've never heard of neural encryption before, do you have a good source for me?

From the Wikipedia page for "Neural cryptography", it seems like there's some success in using NN's for cryptanalysis, but not for constructions...

Edit: Do you mean the Google GAN experiment? (https://arxiv.org/pdf/1610.06918v1.pdf) Ahh ok, well at least for this there looks like an attempt at defining a security model (security against some other NN). I don't really believe the security model is realistic (how do we know NN's are really that effective as adversaries?), but at least there is a model, so calling that "encryption" sits somewhat better with me. I'm pretty sure this is not what's being used by Numerai since it seems like it would not result in ciphertexts with the structure necessary to perform ML operations on.

Edit2: Maybe you're right and it is more advanced. In any case, as a crypto nerd I wish they would disclose what they are actually doing / the rationale instead of tantalizingly suggesting that they have made (what would be) a breakthrough in a practical use case of advanced encryption schemes, but not saying how.

[sandGorgon]

That particular paper got a LOT of flames when it was posted to /r/MachineLearning

https://www.reddit.com/r/MachineLearning/comments/59v9ua/r_1...