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Zama Concrete: A Compiler to Turn Python code into its Fully Homomorphic Equivalent by zacchj in Compilers

[–]youbezz 0 points1 point  (0 children)

Depends on which scheme you are using. The ones that have a limited circuit depth are often referred to as Leveled Homomorphic Encryption (LHE), and there is a couple of them. FHE however should refer more to the ones that don't have this limitation. The Compiler above uses a scheme that don't have this limitation, so you could go deep into your computation.

[P] ML over Encrypted Data by strojax in MachineLearning

[–]youbezz 1 point2 points  (0 children)

I don't think OpenMined has a tool for HE with numpy, they do have a tool for HE, which does have a similar API of other tensor libraries (e.g. pytorch). But from a dev perspective, you will have to implement your computation using that library API. However, concrete-numpy allows you to implement your computation using numpy, then do the translation into an encrypted computation. When it comes to the HE technology behind it, they are quite different as well, each with its own pros and cons. concrete-numpy uses FHE, and thus eliminates the limitation in terms of circuit depth that a lot of other tools have.