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by lkowalcz
3236 days ago
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Worth pointing out that Numerai actually doesn't use encryption in any standard sense (including structure-preserving encryption), but instead seems to be using some heuristic method of obfuscating their data. Their (closed-source) method of obfuscating their data apparently does have the property that it preserves the structure of the data, but calling it "structure-preserving encryption" is misleading imo since it risks confusing it with standard notions of encryption and structure-preserving encryption which have much stronger security guarantees. (Their marketing seems to encourage this conflation by, for example, citing academic advances in standard notions of homomorphic encryption and SPE and implying that these advances have enabled Numerai's technology) https://medium.com/numerai/encrypted-data-for-efficient-mark... |
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> 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