fully-homomorphic-encryption

The first link has a misleading name. Instead use these two links for a better picture: https://github.com/google/fully-homomorphic-encryption/tree/... https://fhe-benchmarking.github.io/

I don't have any advice for you, but I do work on homomorphic encryption at Google and we have an FHE compiler project [1] (though it is likely going to change a lot in the coming year). I happen to have a math PhD, so the transition to this field was not a huge stretch, but before that I worked in supply chain optimization for data centers, and just decided this was too exciting to pass up. [1]: https://github.com/google/fully-homomorphic-encryption/issue...

+1, and some compilers already exist to do that for you. See, e.g., Google's compiler (which I work on). https://github.com/google/fully-homomorphic-encryption

Whilst demonstrating incredible bleeding edge technology, the Hangman example is hardcoded. https://github.com/google/fully-homomorphic-encryption/blob/... It's such a convenient parody of a classic programming exercise that it must be intentional. I can't help laughing at how that one file is saying two things at once: "Uh, it's one-word Hangman. Dead simple. Nothing up our sleeves. I have Real Stuff to do, give me a break." "Our product is working great, but there's some minor fixes to do. Let's hold a meeting on how to really get this multi-word support cracked. Maybe add 'privacy-aware' and 'digitalization'?" Surprisingly, it's also making it very easy to understand what is actually relevant in the project.

Are there any benchmarks to estimate its usability? I first encountered FHE many years ago, but while the concept is cool, the performance hit (IIRC I saw literally a million times slowdown back then) made it absolutely impractical for non-toy problems. And whenever I see reports, they tend to note that it's slow, just as this project (https://github.com/google/fully-homomorphic-encryption/tree/...) notes "the run-times of the FHE-C++ operations are likely to be too long to be practical at this time.", it does not provide any data on just how slow it is. Are there measurements on how long the demos take to execute, so that I can evaluate if it has the potential for some specific idea without having to set up the build system to try it out myself? E.g. run the same string capitalization demo on 100, 10 000 and 1 000 0000 characters to benc

See https://github.com/google/fully-homomorphic-encryption/tree/... - "Variable-length arrays are not supported" - "While-loops and for-loops with a variable end-condition are not supported." - "Floating-point data types are not supported."

It has a dependency on XLS[cc], so they share their limitations: https://github.com/google/fully-homomorphic-encryption/tree/...

whitepaper: https://github.com/google/fully-homomorphic-encryption/blob/...