Comment by littlecranky67
6 months ago
I get how that works for arithmetic operations - what about stuff like sorting, finding an element in a set etc? This would require knowledge of the cleartext data, wouldn't it?
6 months ago
I get how that works for arithmetic operations - what about stuff like sorting, finding an element in a set etc? This would require knowledge of the cleartext data, wouldn't it?
You can reduce anything happening on the computer to arithmetic operations. If you can do additions and multiplications, then it's turing complete. All others can be constructed from them.
While correct, that doesn't answer the question at all, though. If I have my address book submited into an FHE system and want to sort by name - how do you do that if the FHE system does not have access to cleartext names?
You can do that by encrypting the names. You send encrypted names to the FHE-server, and then the server does necessary sorting computations on it.
The point of FHE is it can operate on gibberish-looking ciphertext, and when this ciphertext decrypted afterwards, the result is correct.
Indeed, there are those working on faster FHE sorting: https://eprint.iacr.org/2021/551.pdf
When comparing two ciphertexts A,B a FHE sorting function will output a sorted pair of two new ciphertexts:
E.g. FHE_SORT(A,B) -> (X,Y)
where Dec(X)<Dec(Y)
But without decoding, there's no way of knowing whether X (or Y) comes from A or B.
Source: II. D of https://eprint.iacr.org/2015/995.pdf
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Honestly it breaks my brain as well. I just have to take it on trust that it apparently works.
Comparisons can be implemented by approximating a < b with
And the sign function can be approximated by a polynomial that uses only additions and multiplications and products with constants.
Other FHE schemes have support for small-bitwidth lookup tables that makes supporting comparison more direct.