5 ms·
I don't think you can apply the model (with unencrypted outputs) without all the decryption keys.
by TTPrograms 8y ago
I don't think you can apply the model (with unencrypted outputs) without all the decryption keys.
- olliej 8y agoThe point of the paper was to operate over data without decrypting, the exact scenario they gave was competing finance companies, that are clearly not going to share keys. Also if you had all of the decryption keys you’d just decrypt the data and use the raw data. They explicitly state that it is only fast in the context of HE problems - being multiple orders of magnitude slower than techniques you can use on raw data (they actually said “fast” - complete with the quotes, which I appreciated)
- TTPrograms 8y agoI agree the example is weird, but that's literally what the paper says: "In the training phase, it takes as input an encrypted training data and outputs an encrypted model without using the decryption key. In the prediction phase, it uses the encrypted model to predict results on new encrypted data." Figure 1 further implies that the results must be decrypted. This is the typical operational setting of homomorphic ML.