The application discloses a
network security vulnerability knowledge graph construction method based on HPO-BiLSTM-CRF, which comprises the following steps: collecting public
vulnerability data from related databases in the network space security field, preprocessing, and constructing a
data set; analyzing and extracting existing
data source feature information, and constructing a
network security vulnerability domain ontology model CSVDO; based on the optimized bidirectional long short-
term memory network and the
conditional random field fusion model HPO-BiLSTM-CRF, realizing
named entity recognition and
relationship extraction; adopting an integrated entity alignment method for knowledge fusion, matching different instances of the same object in different ontologies based on an improved similarity measurement
algorithm, and constructing a
knowledge graph; carrying out
knowledge graph embedding, storing the result into a
graph database, and completing knowledge graph construction and graphic
visualization. The application can improve the efficiency of entity recognition and
relationship extraction in
network security vulnerability knowledge, and has the advantages of high efficiency and high accuracy compared with other graph construction methods.