The application discloses a
machine learning-based digital twin dynamic optimization method, device and medium, relates to the technical field of
network security, and solves the problem that a to-be-optimized node in a network cannot be accurately screened based on an influence degree. The method comprises the following steps: acquiring
network structure data and historical abnormal data of a target network, and mapping the target network to a
digital network space according to the
network structure data and the historical abnormal data; analyzing different transmission nodes in the
digital network space; analyzing different transmission nodes in the
digital network space according to the historical abnormal data, to obtain a first transmission node and a second transmission node; analyzing the first transmission node and the second transmission node, to obtain a to-be-optimized node in the digital network space; and optimizing a corresponding network node in the target network according to the to-be-optimized node in the digital network space. The application realizes accurate screening of a to-be-optimized node in a network based on an influence degree.