Create a way to load encrypted models efficiently?

[elephantpanda]

If I have a customised onnx model possibly trained on my own copyrighted images, I would like to find a way to encrypt it. Then run the encrypted model.

Yes, I could use a 3rd party encrypter, but I'm thinking for a very big model of 1GB, if I decrypt it I will have to use up 1GB of RAM. And computers are already short of RAM to run the models.

What I would like is a function like EncryptedInferenceSession("model.onnx.encrypted", secret_key) which would load the enctypted model onto the GPU in a memory saving way using a secret key.

Alternatively a way to load the model bit by bit in manageable chunks like 50Mb each. And decrypt each one on the fly.

Either of these would be a valid solution.

[RyanUnderhill]

I'd recommend using the API that loads a model from memory: CreateSessionFromArray https://onnxruntime.ai/docs/api/c/struct_ort_api.html#a8c9d4f617fd806cd10da1fecd265dd8c

This way you can decrypt it any way you choose and just pass a pointer to the decrypted model, it doesn't need to be a file.

[elephantpanda]

Thanks I'll give it a go!