https://en.m.wikipedia.org/wiki/Homomorphic_encryption
I'm not sure how the author jumped to the conclusions they did, but they show a severe misunderstanding of the applications of homomorphic encryption
https://en.m.wikipedia.org/wiki/Homomorphic_encryption
I'm not sure how the author jumped to the conclusions they did, but they show a severe misunderstanding of the applications of homomorphic encryption
With regard to FHE, I'm familiar with the concept in abstract, but this article and the comments made me wonder how traditional definitions of security work in a homomorphic world.
Specifically, do we assume under FHE that the computation provider has no a-priori information beyond basic structure of the values contained? (i.e. do you need to exchange some key to the party who should be able to do computation, even if this key can't decrypt the ciphertext to plaintext?)
Assuming this isn't the case, do we retain classical definitions of security (the ciphertext leaks no information about plaintext; large collections of ciphertexts similarly reveal no information about plaintexts, or the similarity or difference between any two plaintexts) under FHE?
It seems if this holds true, FHE mathematically can't do this, as it would require revealing information from a ciphertext that means it is no longer effectively encrypted, hence it isn't homomorphic.
However, in practice, you reveal some information about the data if you do computations in it. One notional example is if you see a bunch of XORs in data. You may not know what the data is, but if you see a bunch of XORs, you can make an educated guess that some sort of cipher operation occurs (as XOR is used heavily in it).
https://github.com/tf-encrypted/tf-encrypted
Homomorphic means the algebra is the same on both sides of the encryption, so this would be one of the types of encryption where this is possible.
In reading through the readme, its data the user encrypts (which is a goal of homomorphic encryption), not learning on data of someone else that is encrypted.
Assuming data us properly encrypted, it is indistinguishable from noise, so I don't see how someone can learn on someone else's encrypted data.
It's all about homologies, understand what that means to understand why this is possible while still having good security and doing encryption correctly.