ISSRE // 2025

ISGraphVD: Precise Vulnerability Detection for IoT Supply Chains Based on Identifier Sensitive Graph

Yingli Zhang // Xin Liu // Ziang Liu // Song Li // Nan Li // Weina Niu // Rui Zhou // Qingguo Zhou

ISGraphVD studies precise vulnerability detection in IoT supply chains using identifier-sensitive graph modeling, targeting more accurate analysis of component relationships and vulnerability propagation.

Paper

Overview

This work targets vulnerability detection in IoT-oriented software supply chains. It emphasizes identifier-sensitive graph construction so that analysis can better preserve the semantic relations needed for precise detection.

Research context

The paper sits at the intersection of supply chain security, program analysis, and trustworthy software engineering, complementing Ziang Liu’s work on compliance analysis with security-oriented dependency reasoning.

Citation

@inproceedings{zhang2025isgraphvd,
  author = {Zhang, Yingli and Liu, Xin and Liu, Ziang and Li, Song and Li, Nan and Niu, Weina and Zhou, Rui and Zhou, Qingguo},
  title = {ISGraphVD: Precise Vulnerability Detection for IoT Supply Chains Based on Identifier Sensitive Graph},
  booktitle = {2025 IEEE 36th International Symposium on Software Reliability Engineering ({ISSRE})},
  pages = {83--94},
  year = {2025},
  publisher = {{IEEE}},
  doi = {10.1109/ISSRE66568.2025.00021}
}

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