Distributed Training in Access Control Model

Abstract

Classification and regression prediction of access objects in distributed access control model is a very important basic task in distributed access control model. Machine learning plays an important role in the field of intelligent access control in the future, especially in the application of machine learning methods to solve classification and regression problems. The paper proposes a learning method of distributed collaborative training, which can reduce the communication consumption of node policy update and increase the access execution margin of a single node. Improve model performance