The number of new vulnerabilities continues to rise significantly each year. Simultaneously,
vulnerability databases have challenges in promptly sharing new security events with …

The increasing reliance on computer networks and blockchain technology has led to a
growing concern for cybersecurity and privacy. The emergence of zero-day vulnerabilities …

This paper provides a comprehensive review of the future of cybersecurity through
Generative AI and Large Language Models (LLMs). We explore LLM applications across …

A core problem of vulnerability detection is to detect multi-type vulnerabilities simultaneously
by characterizing vulnerabilities of high diversity and complexity in real program source …

Vulnerabilities in the source code are one of the main causes of potential threats in software-
intensive systems. There are a large number of vulnerabilities published each day, and …

Background: The C/C++ languages hold significant importance in Software Engineering
research because of their widespread use in practice. Numerous studies have utilized …

Recently, deep learning-based software vulnerability detection (SVD) approaches have
achieved promising performance. However, the scarcity of high-quality labeled SVD data …

Software vulnerabilities can result in catastrophic cyberattacks that increasingly threaten
business operations. Consequently, ensuring the safety of software systems has become a …

The growing complexity and volume of modern software have led to an increase in source
code vulnerabilities, posing significant security risks. In response, deep learning-based …

Code linters play a crucial role in developing high-quality software systems by detecting
potential problems (eg, memory leaks) in the source code of systems. Despite their benefits …