The application discloses a
network routing mechanism
vulnerability analysis method based on a graph neural network and a
knowledge graph, which comprises the following steps: simulating the
network routing mechanism
vulnerability analysis of a target low-
orbit interconnected
network topology node based on a graph neural network and a
knowledge graph; performing a
fault injection experiment on a routing program in the simulated
network topology; dynamically collecting
vulnerability information of the
network routing mechanism; and constructing a network routing mechanism vulnerability dataset; constructing a network routing mechanism vulnerability domain ontology NRMVO based on four dimensions of assets, networks,
software and vulnerabilities; performing
knowledge extraction on a program for realizing network routing; analyzing the relevance between complex structure information of the routing program and vulnerability of the network routing program; and constructing a target low-
orbit interconnected network routing mechanism vulnerability
knowledge graph; storing the result in a
graph database; realizing knowledge graph
visualization; constructing a target network routing mechanism vulnerability analysis model HGAT-BNR; and analyzing the vulnerability of the network routing mechanism from four dimensions of data flow,
control flow, calling flow and access flow. The application has the advantages of high efficiency and high accuracy, and provides an effective
analysis method for improving the reliability and security of the network routing mechanism.