4 ms·
> Once the model is trained, I can run this on any data encrypted with key X and find out if the data contains a cat (with some degree of accuracy). I have no w
by KenoFischer 7y ago
> Once the model is trained, I can run this on any data encrypted with key X and find out if the data contains a cat (with some degree of accuracy). I have no way of telling information outside the tags provided on the training data, but it still gives me, a person without the encryption key, the ability to identify any feature that's tagged in the training set on any un-tagged production set.
I think you're missing the fact that the predictions come back encrypted, so you don't learn anything unless you know the key. Also, in this particular example the model was trained on unencrypted data, but as discussed below, you can do either.
- falcolas 7y agoPredictions are a tag, and a separate confidence value. A fairly finite set. Cat. Not a Cat. Large quantities of small finite sets are anathema to encryption.
- KenoFischer 7y agoI'm still only guessing at the objection, but if it helps, the encryptions are randomized, so two different encryptions of the same value do not have the same ciphertext.
- heavenlyblue 7y agoNot all encryption algorithms are susceptible to known-cyphertext attacks.
- heavenlyblue 7y agoIf you map a binary variable into a, let's say, 128-bit number (non-linearly) where a mapping is unique for every encryption key used, there's nothing making it an anathema for encryption. I am not sure whether this is achievable practically though.