摘要
Abstract
Software vulnerabilities pose significant threats to systems.Traditional vulnerability remediation methods rely on manual intervention,which is not only time-consuming and labor-intensive but also prone to introducing new vulnerabilities.With the rapid development of machine learning and deep learning,learning-based automated vulnerability remediation techniques have gradually become a research hotspot.These techniques aim to assist developers in quickly identifying and fixing vulnerabilities,thereby reducing the losses caused by vulnerabilities.This paper provides a comprehensive review of existing learning-based automated vulnerability remediation concepts,repair processes,and related technologies.It analyzes the research progress,challenges faced,and proposes future research directions and potential solutions.关键词
软件漏洞/漏洞自动修复/深度学习/网络安全/软件系统Key words
software vulnerability/automatic vulnerability remediation/deep learning/cybersecurity/software systems分类
信息技术与安全科学
