nexflatline OP t1_j1y6woz wrote

The dataset is secured, no problems with that, but someone could take the model and use it as it is. Our model is trained and runs on a popular open source framework, which we advertise as a feature since many people are familiar with how well it works already. Our main "product" is the model itself, made by painstakingly labeling hundreds of thousands of videos manually. Unfortunately deep learning models are not considered algorithms here and cannot be patented at the moment. So all we can do is hide it.


nexflatline OP t1_j1xy26j wrote

Thank you for the tips. If I may give more details to make the problem clearer: at the moment we already have a cloud architect and the cloud ML system is already up and working. But we are dealing with large amounts of real time video data in high resolution, and that is what makes almost impossible to profit using cloud ML (also the latency is not as good as we expected). For this application we need full-HD video decoding at high frame rates.

The end users are people with no special knowledge of anything computer related and operate all through a mobile application (already done and working). Our idea now is keeping the mobile app, but moving the server locally (a mini-pc installed at the customer location). The problem is that the mini-pc would have the model stored in it and we can't find a way to keep it safe.