Advanced technique for firmware security analysis through heterogeneous data fusion and knowledge mapping.

As the core component of a device, firmware's security directly affects the stability of the entire system and the security of user data. In order to provide a more comprehensive and accurate data foundation and improve the accuracy of firmware security analysis, this article conducts research on advanced technologies for firmware security analysis through heterogeneous data fusion and knowledge mapping. Firstly, preprocess the firmware security analysis knowledge graph data using cleaning, segmentation, classification, and other processing methods. Secondly, calculate the firmware security status value under heterogeneous information based on the processed data; Again, based on the calculation results of firmware security status values, extract knowledge graph features for firmware security analysis and annotate relationship description entries; Finally, based on knowledge mapping technology, ontology integration and ontology mapping knowledge fusion were carried out to achieve more effective organization and representation of firmware security analysis knowledge, and the research on the construction technology of firmware security analysis knowledge graph was completed. The experimental results show that after applying the proposed method for firmware security analysis, the loss function index value and F1 index value are both very high, and the prediction accuracy of knowledge graph evolution is very close to 100%, with good operational effect.