A systematic literature review on automated software vulnerability detection using machine learning
In recent years, numerous Machine Learning (ML) models, including Deep Learning (DL)
and classic ML models, have been developed to detect software vulnerabilities. However …
and classic ML models, have been developed to detect software vulnerabilities. However …
Hierarchical graph-based integration network for propaganda detection in textual news articles on social media
PN Ahmad, J Guo, NM AboElenein, QM Haq… - Scientific Reports, 2025 - nature.com
During the Covid-19 pandemic, the widespread use of social media platforms has facilitated
the dissemination of information, fake news, and propaganda, serving as a vital source of …
the dissemination of information, fake news, and propaganda, serving as a vital source of …
Enhanced Graph Neural Networks for Vulnerability Detection in Java via Advanced Subgraph Construction
Software vulnerability detection (SVD) in source code remains a significant challenge,
capturing the attention of researchers due to its critical importance. Numerous automated …
capturing the attention of researchers due to its critical importance. Numerous automated …
Machine Learning for Cross-Site Scripting (XSS) Detection: A comparative analysis of machine learning models for enhanced XSS detection
B Njie, L Gabriouet - 2024 - diva-portal.org
The objective of this study is to assess the efficacy of several machine learning (ML)
algorithms in identifying cross-site scripting (XSS) vulnerabilities, which are a widespread …
algorithms in identifying cross-site scripting (XSS) vulnerabilities, which are a widespread …