The invention provides a
network security situation awareness method and
system based on a multi-
modal large model, and the method comprises the steps: obtaining the information of a single
data source through an
orthogonal sequence fusion technology, extracting the features of the single
data source through a teacher-student model, carrying out the knowledge
distillation, and carrying out the cross-
modal alignment
processing and fusion
processing; the method comprises the steps of carrying out cross-
modal correlation analysis on multi-
modal data, generating an adversarial sample of the multi-
modal data, calculating an optimal transmission path of features in an
equalization system established by a depth
equalization multi-modal fusion technology, carrying out feature integration, constructing a multi-modal depth
situation awareness and prediction model based on a bidirectional
encoder structure, and carrying out multi-modal depth
situation awareness and prediction. And integrating a residual period prediction technology to carry out
network security situation awareness. According to the method, multi-
modal data of different sources are processed and analyzed, the
network security situation can be comprehensively identified,
complex network attack threats can be identified and defended, the missing report rate and the false report rate of network security
threat identification are reduced, the identification accuracy is improved, and the model
interpretability and transparency are enhanced.