Unveiling Hidden Links Between Unseen Security Entities

arXiv:2403.02014v1 Announce Type: new
Abstract: The proliferation of software vulnerabilities poses a significant challenge for security databases and analysts tasked with their timely identification, classification, and remediation. With the National Vulnerability Database (NVD) reporting an ever-increasing number of vulnerabilities, the traditional manual analysis becomes untenably time-consuming and prone to errors. This paper introduces VulnScopper, an innovative approach that utilizes multi-modal representation learning, combining Knowledge Graphs (KG) and Natural Language Processing (NLP), to automate and enhance the analysis of software vulnerabilities. …

analysis analysts arxiv challenge classification consuming cs.ai cs.cr database databases entities errors hidden identification links national national vulnerability database nvd proliferation remediation reporting security software software vulnerabilities vulnerabilities vulnerability vulnerability database