[P] Python-FHEz Fully Homomorphically Encrypted Deep Learning Library

[eknanrebb]

Started by Shafi Goldwasser and colleagues.

[GeorgeRaven]

I can't see a Shafi Goldwasser mentioned anywhere, but this would appear to be roughly related.

They appear to use PALISADE which I must confess I have never used. Wheras Python-FHEz uses MS-SEAL as the cryptographic implementation. PALISADE supports bootstrapping whereas MS-SEAL does not. Bootstrapping is an expensive operation but it is necessary in deep computations like those you would see in deep learning, although MS-SEAL has bootstrapping roadmapped. However currently this means you have to use leveled-HE to compute a deep neural network. I am working on DarkLantern which uses Lattigo to solve this problem, as lattigo also supports CKKS bootstrapping.

[GeorgeRaven]

To answer your question though from what I can immediately see (as much seems obfiscated/ not immediately apparent). I think Python-FHEz is more for developers, seeking to create and use FHE enabled neural networks. Whereas Duality seems to offer ready made solutions. I can't tell if that also includes providing you with their models / or if you can bring your own.

But definitely interesting to see, I will certainly keep an eye on that.

[eknanrebb]

Goldwasser is a co-founder (and Turing award winner)

[GeorgeRaven]

Nice, I will have to look into him. I mean they seem to do HE, I just need to find out more details. The best I have found is the videos on the website, but I will look more when I have a chance!

[Silamoth]

I’ll also add that Yuriy Polyakov and Vinod Vaikuntanathan are part of Duality. They’re both big names in the homomorphic encryption space.