|Vulnerability Dataset Construction Methods Applied To Vulnerability Detection: A Survey
Vulnerability Detection 2022 - The increasing number of security vulnerabilities has become an important problem that needs to be solved urgently in the ﬁeld of software security, which means that the current vulnerability mining technology still has great potential for development. However, most of the existing AI-based vulnerability detection methods focus on designing different AI models to improve the accuracy of vulnerability detection, ignoring the fundamental problems of data-driven AI-based algorithms: ﬁrst, there is a lack of sufﬁcient high-quality vulnerability data; second, there is no uniﬁed standardized construction method to meet the standardized evaluation of different vulnerability detection models. This all greatly limits security personnel’s in-depth research on vulnerabilities. In this survey, we review the current literature on building high-quality vulnerability datasets, aiming to investigate how state-of-the-art research has leveraged data mining and data processing techniques to generate vulnerability datasets to facilitate vulnerability discovery. We also identify the challenges of this new ﬁeld and share our views on potential research directions.
|Year of Publication
Baltimore, MD, USA
|Google Scholar | BibTeX | DOI