A survey on data-driven software vulnerability assessment and prioritization
Software Vulnerabilities (SVs) are increasing in complexity and scale, posing great security
risks to many software systems. Given the limited resources in practice, SV assessment and …
risks to many software systems. Given the limited resources in practice, SV assessment and …
An empirical comparison of commercial and open‐source web vulnerability scanners
Web vulnerability scanners (WVSs) are tools that can detect security vulnerabilities in web
services. Although both commercial and open‐source WVSs exist, their vulnerability …
services. Although both commercial and open‐source WVSs exist, their vulnerability …
Automated event extraction of CVE descriptions
Context: The dramatically increasing number of vulnerabilities makes manual vulnerability
analysis increasingly more difficult. Automatic extraction of vulnerability information can help …
analysis increasingly more difficult. Automatic extraction of vulnerability information can help …
Efficient feature selection for static analysis vulnerability prediction
Common software vulnerabilities can result in severe security breaches, financial losses,
and reputation deterioration and require research effort to improve software security. The …
and reputation deterioration and require research effort to improve software security. The …
An automatic software vulnerability classification framework using term frequency-inverse gravity moment and feature selection
Vulnerability classification is an important activity in software development and software
quality maintenance. A typical vulnerability classification model usually involves a stage of …
quality maintenance. A typical vulnerability classification model usually involves a stage of …
On the use of fine-grained vulnerable code statements for software vulnerability assessment models
Many studies have developed Machine Learning (ML) approaches to detect Software
Vulnerabilities (SVs) in functions and fine-grained code statements that cause such SVs …
Vulnerabilities (SVs) in functions and fine-grained code statements that cause such SVs …
DeKeDVer: A deep learning-based multi-type software vulnerability classification framework using vulnerability description and source code
Y Dong, Y Tang, X Cheng, Y Yang - Information and Software Technology, 2023 - Elsevier
Context: Software vulnerabilities have confused software developers for a long time.
Vulnerability classification is thus crucial, through which we can know the specific type of …
Vulnerability classification is thus crucial, through which we can know the specific type of …
A survey on automated software vulnerability detection using machine learning and deep learning
Software vulnerability detection is critical in software security because it identifies potential
bugs in software systems, enabling immediate remediation and mitigation measures to be …
bugs in software systems, enabling immediate remediation and mitigation measures to be …
Automated unearthing of dangerous issue reports
The coordinated vulnerability disclosure (CVD) process is commonly adopted for open
source software (OSS) vulnerability management, which suggests to privately report the …
source software (OSS) vulnerability management, which suggests to privately report the …
The random neural network as a bonding model for software vulnerability prediction
Software vulnerability prediction is an important and active area of research where new
methods are needed to build accurate and efficient tools that can identify security issues …
methods are needed to build accurate and efficient tools that can identify security issues …