基于图结构源代码切片的智能化漏洞检测系统

邹德清; 李响; 黄敏桓; 宋翔; 李浩; 李伟明

doi:10.11959/j.issn.2096-109x.2021088

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基于图结构源代码切片的智能化漏洞检测系统

学术论文 | 更新时间：2024-06-03

- 基于图结构源代码切片的智能化漏洞检测系统
- Intelligent vulnerability detection system based on graph structured source code slice
- 网络与信息安全学报 2021年7卷第5期页码：113-122
- 作者机构：
  
  1. 华中科技大学网络空间安全学院，湖北武汉 430074
  2. 信息系统安全技术重点实验室，北京 100101
  3. 华中科技大学软件学院，湖北武汉 430074
  4. 华中科技大学网络与计算中心，湖北武汉 430074
- 作者简介：
  
  [ "邹德清（1975− ），男，湖南浏阳人，华中科技大学教授、博士生导师，主要研究方向为系统与软件安全、云计算安全" ]
  [ "李响（1983− ），女，河北涿州人，信息系统安全技术重点实验室高级工程师，主要研究方向为软件脆弱性分析、恶意代码检测" ]
  [ "黄敏桓（1971− ），男，江西万载人，信息系统安全技术重点实验室研究员，主要研究方向为脆弱性自动分析、网络安全评估与验证" ]
  [ "宋翔（1996− ），男，河南新乡人，华中科技大学硕士生，主要研究方向为网络安全" ]
  [ "李浩（1995− ），男，河南驻马店人，华中科技大学硕士生，主要研究方向为网络安全" ]
  [ "李伟明（1975− ），男，湖南株洲人，华中科技大学副教授，主要研究方向为网络安全" ]
- 基金信息：
  
  国家自然科学基金;The National Nature Science Foundation of China(U1936211)
- DOI：10.11959/j.issn.2096-109x.2021088
  中图分类号： TP393
- 网络首发：2021-10，
  
  纸质出版：2021-10-15
- 稿件说明：
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邹德清, 李响, 黄敏桓, 等. 基于图结构源代码切片的智能化漏洞检测系统[J]. 网络与信息安全学报, 2021,7(5):113-122.

Deqing ZOU, Xiang LI, Minhuan HUANG, et al. Intelligent vulnerability detection system based on graph structured source code slice[J]. Chinese Journal of Network and Information Security, 2021, 7(5): 113-122.
邹德清, 李响, 黄敏桓, 等. 基于图结构源代码切片的智能化漏洞检测系统[J]. 网络与信息安全学报, 2021,7(5):113-122. DOI： 10.11959/j.issn.2096-109x.2021088.

Deqing ZOU, Xiang LI, Minhuan HUANG, et al. Intelligent vulnerability detection system based on graph structured source code slice[J]. Chinese Journal of Network and Information Security, 2021, 7(5): 113-122. DOI： 10.11959/j.issn.2096-109x.2021088.

摘要

针对智能化漏洞检测，从源代码程序依赖图中根据漏洞特征提取图结构源代码切片，将图结构切片信息表征后利用图神经网络模型进行漏洞检测工作。实现了切片级的漏洞检测，并在代码行级预测漏洞行位置。为了验证系统的有效性，分别与静态漏洞检测系统、基于序列化文本信息和基于图结构化信息的漏洞检测系统做比较，实验结果表明，所提系统在漏洞检测能力上有较高准确性，并且在漏洞代码行预测工作上有较好表现。

Abstract

For the intelligent vulnerability detection

the system extracts the graph structured source code slices according to the vulnerability characteristics from the program dependency graph of source code

and then presents the graph structured slice information to carry out vulnerability detection by using the graph neural network model.Slice level vulnerability detection was realized and the vulnerability line was located at the code line level.In order to verify the effectiveness of the system

compared with the static vulnerability detection systems

the vulnerability detection system based on serialized text information

and the vulnerability detection system based on graph structured information

the experimental results show that the proposed system has a high accuracy in the vulnerability detection capability and a good performance in the vulnerability code line prediction.

关键词

Keywords

references

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