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

Peng Xiao¹, Linjiang Xie¹, Feilu Hang¹

¹Information Center of China Southern Power Grid Yunnan Power Grid Co., Ltd, Kunming, Yunnan, 650000, China.

|April 11, 2025

Summary

This study enhances firmware security analysis by fusing heterogeneous data and using knowledge mapping. The new method significantly improves prediction accuracy and operational effectiveness for system stability and data security.

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Area of Science:

Computer Science
Cybersecurity
Data Science

Background:

Firmware security is critical for system stability and user data protection.
Existing firmware security analysis methods lack comprehensive data foundations.

Purpose of the Study:

To advance firmware security analysis through heterogeneous data fusion and knowledge mapping.
To create a more accurate and comprehensive data foundation for firmware security.

Main Methods:

Preprocessing firmware security analysis knowledge graph data (cleaning, segmentation, classification).
Calculating firmware security status values using heterogeneous information.
Extracting knowledge graph features and annotating relationship entries.
Applying knowledge mapping for ontology integration and fusion.

Main Results:

The proposed method achieved very high loss function and F1 index values.
Prediction accuracy for knowledge graph evolution approached 100% with good operational effect.
Effective organization and representation of firmware security analysis knowledge were achieved.

Conclusions:

The developed firmware security analysis knowledge graph construction technology is effective.
Heterogeneous data fusion and knowledge mapping significantly improve firmware security analysis.
The approach provides a robust foundation for enhancing device security and data protection.