Onboard firmware extraction method based on circuit semantic analysis

CN120689882APending Publication Date: 2025-09-23MILITARY SECRECY QUALIFICATION EXAMINATION & CERTIFICATION CENT
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Patent Information

Application Number
CN202510685937.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-05-27
Publication Date
2025-09-23

AI Technical Summary

Technical Problem

Existing technologies have problems with low efficiency, poor accuracy, and insufficient automation in extracting firmware from industrial control equipment. In particular, it is difficult to achieve multi-scale feature extraction when identifying irregularly packaged chips and complex backgrounds. It also lacks effective semantic extension and long-sequence dependency modeling capabilities, resulting in vulnerability detection delays and difficulty in ensuring security.

Method used

A multi-stage collaborative method based on circuit semantic analysis is adopted, including image acquisition, preprocessing, semantic recognition, model matching, firmware extraction and deep learning. Through the combination of image processing and deep learning, the automatic acquisition of chip information and firmware function analysis are realized. Depthwise convolution and ReLU6 activation function are used for sequence prediction and semantic analysis.

Benefits of technology

It significantly improves the accuracy of chip model matching and firmware function identification, shortens firmware extraction time, reduces labor costs, and improves the coverage and security of vulnerability detection.

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Abstract

The invention belongs to the technical field of electric signal processing, data characterization and signal classification, and relates to an onboard firmware extraction method based on circuit semantic analysis, which comprises the following steps: acquiring an image of an onboard chip and a connection relationship by using firmware extraction equipment; preprocessing the acquired image to obtain a preprocessed image; performing semantic recognition on the preprocessed image to obtain a primary feature; performing model matching and semantic extension based on the preprocessed image and the primary features to obtain advanced features; according to the advanced features, using a probe or a connecting line to connect a chip pin with firmware extraction equipment; using firmware reading equipment and tools to extract firmware data from the chip; carrying out stack self-coding on the extracted firmware data, and outputting self-coded data; performing sequence prediction and semantic analysis on the self-coded data to obtain a firmware function and process; according to the method, automatic acquisition of chip information and firmware function analysis are realized based on model matching and semantic extension.
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