5 citations · 7 across the 13 of their papers we have counts for
14 papers
Vulnerable Models in the AI Supply Chain: An Empirical Study of Adoption, Propagation, and Usage Patterns
The Anh Nguyen, Triet Huynh Minh Le, M. Ali Babar
The rapid integration of Artificial Intelligence (AI) models has established a complex supply chain, but many of these shared artifacts harbor severe vulnerabilities such as insecu…
Securing the AI Supply Chain: What Can We Learn From Developer-Reported Security Issues and Solutions of AI Projects?
The Anh Nguyen, Triet Huynh Minh Le, M. Ali Babar
The rapid growth of Artificial Intelligence (AI) models and applications has led to an increasingly complex security landscape. Developers of AI projects must contend not only with…
Software Vulnerability Management in the Era of Artificial Intelligence: An Industry Perspective
M. Mehdi Kholoosi, Triet Huynh Minh Le, M. Ali Babar
Artificial Intelligence (AI) has revolutionized software development, particularly by automating repetitive tasks and improving developer productivity. While these advancements are…
VulGuard: An Unified Tool for Evaluating Just-In-Time Vulnerability Prediction Models
Duong Nguyen, Manh Tran-Duc, Thanh Le-Cong +3
We present VulGuard, an automated tool designed to streamline the extraction, processing, and analysis of commits from GitHub repositories for Just-In-Time vulnerability prediction…
Toward Realistic Evaluations of Just-In-Time Vulnerability Prediction
Duong Nguyen, Thanh Le-Cong, Triet Huynh Minh Le +2
Modern software systems are increasingly complex, presenting significant challenges in quality assurance. Just-in-time vulnerability prediction (JIT-VP) is a proactive approach to…
LLMSecConfig: An LLM-Based Approach for Fixing Software Container Misconfigurations
Ziyang Ye, Triet Huynh Minh Le, M. Ali Babar
Security misconfigurations in Container Orchestrators (COs) can pose serious threats to software systems. While Static Analysis Tools (SATs) can effectively detect these security v…
Multivariate Time Series Anomaly Detection by Capturing Coarse-Grained Intra- and Inter-Variate Dependencies
Yongzheng Xie, Hongyu Zhang, Muhammad Ali Babar
Multivariate time series anomaly detection is essential for failure management in web application operations, as it directly influences the effectiveness and timeliness of implemen…
MVD: A Multi-Lingual Software Vulnerability Detection Framework
Boyu Zhang, Triet H. M. Le, M. Ali Babar
Software vulnerabilities can result in catastrophic cyberattacks that increasingly threaten business operations. Consequently, ensuring the safety of software systems has become a…
Automated Code-centric Software Vulnerability Assessment: How Far Are We? An Empirical Study in C/C++
Anh The Nguyen, Triet Huynh Minh Le, M. Ali Babar
Background: The C and C++ languages hold significant importance in Software Engineering research because of their widespread use in practice. Numerous studies have utilized Machine…
Automatic Data Labeling for Software Vulnerability Prediction Models: How Far Are We?
Triet H. M. Le, M. Ali Babar
Background: Software Vulnerability (SV) prediction needs large-sized and high-quality data to perform well. Current SV datasets mostly require expensive labeling efforts by experts…
Systematic Literature Review on Application of Learning-based Approaches in Continuous Integration
Ali Kazemi Arani, Triet Huynh Minh Le, Mansooreh Zahedi +1
Context: Machine learning (ML) and deep learning (DL) analyze raw data to extract valuable insights in specific phases. The rise of continuous practices in software projects emphas…
Software Vulnerability Prediction in Low-Resource Languages: An Empirical Study of CodeBERT and ChatGPT
Triet H. M. Le, M. Ali Babar, Tung Hoang Thai
Background: Software Vulnerability (SV) prediction in emerging languages is increasingly important to ensure software security in modern systems. However, these languages usually h…
LogSD: Detecting Anomalies from System Logs through Self-supervised Learning and Frequency-based Masking
Yongzheng Xie, Hongyu Zhang, Muhammad Ali Babar
Log analysis is one of the main techniques that engineers use for troubleshooting large-scale software systems. Over the years, many supervised, semi-supervised, and unsupervised l…
Are Latent Vulnerabilities Hidden Gems for Software Vulnerability Prediction? An Empirical Study
Triet H. M. Le, Xiaoning Du, M. Ali Babar
Collecting relevant and high-quality data is integral to the development of effective Software Vulnerability (SV) prediction models. Most of the current SV datasets rely on SV-fixi…