Private function evaluation using machine learning

A system, comprising:

• a computing device;
• and
• a computer-readable storage device coupled to the computing device and having instructions stored thereon which, when executed by the computing device, cause the computing device to perform operations comprising:
• identifying a function provided by a function-providing entity;
• training a neural network to approximate the function;
• generating a shallow neural network from the neural network, wherein the shallow neural network approximates the function and includes shallow network parameters;
• secret sharing the shallow network parameters to a first set of entities;
• receiving a request to execute the function using at least one input parameter;
• secret sharing the at least one input parameter to the first set of entities;
• receiving secret-shared function outputs generated by the first set of entities using a set of secret-shared input parameters and the shallow neural network with secret-shared shallow network parameters;
• generating a function output for the function using the secret-shared function outputs;
• and
• providing the function output in response to the request to execute the function.

A non-transitory computer-readable storage medium coupled to one or more processors and having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations comprising:

• identifying a function provided by a function-providing entity;
• training a neural network to approximate the function;
• generating a shallow neural network from the neural network, wherein the shallow neural network approximates the function and includes shallow network parameters;
• secret sharing the shallow network parameters to a first set of entities;
• receiving a request to execute the function using at least one input parameter;
• secret sharing the at least one input parameter to the first set of entities;
• receiving secret-shared function outputs generated by the first set of entities using a set of secret-shared input parameters and the shallow neural network with secret-shared shallow network parameters;
• generating a function output for the function using the secret-shared function outputs;
• and
• providing the function output in response to the request to execute the function.