A dual graph neural networks model using sequence embedding as graph nodes for vulnerability detection-Reference-Cited by-同舟云学术

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A dual graph neural networks model using sequence embedding as graph nodes for vulnerability detection

Published:2025-01 Issue: Volume:177 Page:107581
ISSN:0950-5849
Container-title:Information and Software Technology
language:en
Short-container-title:Information and Software Technology

Author:

Ling Miaogui,Tang Mingwei,Bian Deng,Lv Shixuan,Tang Qi

Funder

Key Research and Development Program of Sichuan Province

Xihua University

Innovative Research Group Project of the National Natural Science Foundation of China

Sichuan Province Science and Technology Support Program

Science and Technology Bureau of Chengdu

Publisher

Elsevier BV

Reference52 articles.

1. National Vulnerability Database,2023

2. Automated vulnerability detection in source code using deep representation learning;Russell,2018

3. Vuldeepecker: A deep learning-based system for vulnerability detection;Li,2018

4. Deepwukong: Statically detecting software vulnerabilities using deep graph neural network;Cheng;ACM Trans. Softw. Eng. Methodol. (TOSEM),2021

5. Devign: Effective vulnerability identification by learning comprehensive program semantics via graph neural networks;Zhou;Adv. Neural Inf. Process. Syst.,2019

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