Discernment and Perusal of Software Vulnerability

Abstract

The examination of vulnerabilities is vital to network security, and finding the route to the flaw's source is essential for the analysis and mitigation of software vulnerabilities that attackers can exploit. The automation of secure software development can be easily achieved by using vulnerability ID. Prior to this, manually tagged communications with vulnerability ID was a laborious process that had scalability problems and room for human mistakes. To facilitate code examination, several vulnerability detection techniques have been developed and to support code inspection, several vulnerability detection techniques have been developed. A series of research that uses machine learning approaches and provide encouraging outcomes are among these strategies. This chapter discusses recent research trend that uses deep learning to identify vulnerabilities and demonstrates how cutting-edge neural approaches are used to identify potentially problematic code patterns. It also highlights a few publications from research that have analyzed vulnerability identification using deep learning.