Fast and Private Inference of Deep Neural Networks by Co-designing Activation Functions

arXiv:2306.08538v2 Announce Type: replace-cross
Abstract: Machine Learning as a Service (MLaaS) is an increasingly popular design where a company with abundant computing resources trains a deep neural network and offers query access for tasks like image classification. The challenge with this design is that MLaaS requires the client to reveal their potentially sensitive queries to the company hosting the model. Multi-party computation (MPC) protects the client's data by allowing encrypted inferences. However, current approaches suffer from prohibitively large inference times. …

abstract access arxiv challenge classification client computing computing resources cs.cr cs.lg deep neural network design designing functions image inference machine machine learning network networks neural network neural networks popular query resources service tasks trains type