软件安全漏洞自动检测与修复技术研究
摘 要
随着信息技术的迅猛发展，软件安全漏洞成为威胁网络安全的关键因素，针对软件安全漏洞的传统检测与修复方法存在效率低、成本高、难以应对复杂多变漏洞等问题。本研究旨在构建一种高效准确的软件安全漏洞自动检测与修复技术体系，以提升软件安全性。基于静态分析和动态分析相结合的方法，利用程序依赖图等技术对源代码进行深度解析，挖掘潜在的安全漏洞；同时引入机器学习算法，通过训练大量已知漏洞样本，建立智能检测模型，实现对未知漏洞的有效预测。在修复方面，设计了一种基于补丁模式库的自动化修复框架，能够根据检测到的漏洞类型自动生成修复方案并实施修复操作。实验结果表明，该技术体系能够显著提高软件安全漏洞检测的准确率和召回率，平均检测时间较传统方法缩短约30%，修复成功率超过85%。
关键词：软件安全漏洞 自动检测与修复 静态与动态分析
Abstract
With the rapid development of information technology, software security vulnerabilities have become a key factor threatening network security. The traditional detection and repair methods for software security vulnerabilities have problems such as low efficiency, high cost, and difficulty to deal with complex and changeable vulnerabilities. The purpose of this study is to build an efficient and accurate automatic software security vulnerability detection and repair technology system to improve software security. Based on the combination of static analysis and dynamic analysis, the source code is deeply analyzed to explore potential security vulnerabilities; and the machine learning algorithm is introduced to train a large number of known vulnerability samples and establish intelligent detection model to realize effective prediction of unknown vulnerabilities. In terms of repair, an automated repair fr amework based on patch pattern library is designed, which can automatically generate repair schemes and implement repair operations according to the type of vulnerability detected. The experimental results show that the technical system can significantly improve the accuracy and recall rate of software security vulnerability detection, the average detection time is about 30% shorter than the traditional method, and the repair success rate is more than 85%.
Keyword:Software Security Vulnerability Automatic Detection And Repair Static And Dynamic Analysis
目 录
1绪论 1
1.1研究背景与意义 1
1.2国内外研究现状 1
1.3本文研究方法 2
2软件安全漏洞检测技术 2
2.1漏洞检测原理与方法 2
2.2静态分析技术研究 3
2.3动态分析技术研究 3
3自动修复技术探索 4
3.1修复技术概述 4
3.2基于模式的修复方法 4
3.3基于机器学习的修复 5
4检测与修复系统构建 6
4.1系统架构设计 6
4.2关键模块实现 6
4.3系统性能评估 7
结论 7
参考文献 9
致谢 10
摘 要
随着信息技术的迅猛发展，软件安全漏洞成为威胁网络安全的关键因素，针对软件安全漏洞的传统检测与修复方法存在效率低、成本高、难以应对复杂多变漏洞等问题。本研究旨在构建一种高效准确的软件安全漏洞自动检测与修复技术体系，以提升软件安全性。基于静态分析和动态分析相结合的方法，利用程序依赖图等技术对源代码进行深度解析，挖掘潜在的安全漏洞；同时引入机器学习算法，通过训练大量已知漏洞样本，建立智能检测模型，实现对未知漏洞的有效预测。在修复方面，设计了一种基于补丁模式库的自动化修复框架，能够根据检测到的漏洞类型自动生成修复方案并实施修复操作。实验结果表明，该技术体系能够显著提高软件安全漏洞检测的准确率和召回率，平均检测时间较传统方法缩短约30%，修复成功率超过85%。
关键词：软件安全漏洞 自动检测与修复 静态与动态分析
Abstract
With the rapid development of information technology, software security vulnerabilities have become a key factor threatening network security. The traditional detection and repair methods for software security vulnerabilities have problems such as low efficiency, high cost, and difficulty to deal with complex and changeable vulnerabilities. The purpose of this study is to build an efficient and accurate automatic software security vulnerability detection and repair technology system to improve software security. Based on the combination of static analysis and dynamic analysis, the source code is deeply analyzed to explore potential security vulnerabilities; and the machine learning algorithm is introduced to train a large number of known vulnerability samples and establish intelligent detection model to realize effective prediction of unknown vulnerabilities. In terms of repair, an automated repair fr amework based on patch pattern library is designed, which can automatically generate repair schemes and implement repair operations according to the type of vulnerability detected. The experimental results show that the technical system can significantly improve the accuracy and recall rate of software security vulnerability detection, the average detection time is about 30% shorter than the traditional method, and the repair success rate is more than 85%.
Keyword:Software Security Vulnerability Automatic Detection And Repair Static And Dynamic Analysis
目 录
1绪论 1
1.1研究背景与意义 1
1.2国内外研究现状 1
1.3本文研究方法 2
2软件安全漏洞检测技术 2
2.1漏洞检测原理与方法 2
2.2静态分析技术研究 3
2.3动态分析技术研究 3
3自动修复技术探索 4
3.1修复技术概述 4
3.2基于模式的修复方法 4
3.3基于机器学习的修复 5
4检测与修复系统构建 6
4.1系统架构设计 6
4.2关键模块实现 6
4.3系统性能评估 7
结论 7
参考文献 9
致谢 10
