Securely Exposing Machine Learning Models to Web Clients using Intel SGX

Machine Learning (ML) methods are applied frequently to predict outcomes or features, that would otherwise require tedious manual work. ML models are usually deployed on Web servers, where end user can query them providing the input data. Server side deployment's shortcoming is that users' data must be sent to a server on each query, increasing network usage and leading to privacy/legal issues. In this paper we present a system which aims to ease the deployment of ML models on the client side of Web applications, while protecting the Intellectual Property (IP) of the model owner. Protection of the ML model is realized with Intel SGX which assures that a loaded model cannot be inspected by the end-user.