Managing use of inference models trained to reduce reconstructability of input features

Abstract

Methods, systems, and devices for providing computer-implemented services are disclosed. To provide the computer-implemented services, inference models may be deployed to locations to generate inferences. Prior to deploying an inference model to a location, it may be determined whether the location is trustworthy. If the location is determined to not be trustworthy, an input data attack resistant inference model may be selected and deployed. The input data attack resistant inference model may be based, at least in part, on a training process that includes a weight freezing process based on levels of reconstructability of input features based on inferences generated by the input data attack resistant inference model. The training process may decrease a likelihood of the inferences generated by the input data attack resistant inference model being usable to reconstruct input data used to generate the inferences. By doing so, sensitive input data may be protected during inference generation.