Publications (43)
Agents at Risk: How Users Unwittingly Undermine LLM Safety
Fengchao Chen, Tingmin Wu, Van Nguyen +2
Large language model (LLM)-based agents are increasingly deployed in applications, such as trip-planning agents and web-use agents, to perform complex planning and execution tasks.…
Cross Project Software Vulnerability Detection via Domain Adaptation and Max-Margin Principle
Van Nguyen, Trung Le, Chakkrit Tantithamthavorn +3
Software vulnerabilities (SVs) have become a common, serious and crucial concern due to the ubiquity of computer software. Many machine learning-based approaches have been proposed…
PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models
Fengchao Chen, Tingmin Wu, Van Nguyen +3
Phishing remains a pervasive cyber threat, as attackers craft deceptive emails to lure victims into revealing sensitive information. While Artificial Intelligence (AI), in particul…
AIBugHunter: A Practical Tool for Predicting, Classifying and Repairing Software Vulnerabilities
Michael Fu, Chakkrit Tantithamthavorn, Trung Le +4
Many ML-based approaches have been proposed to automatically detect, localize, and repair software vulnerabilities. While ML-based methods are more effective than program analysis-…
Self-supervised Activity Representation Learning with Incremental Data: An Empirical Study
Jason Liu, Shohreh Deldari, Hao Xue +2
In the context of mobile sensing environments, various sensors on mobile devices continually generate a vast amount of data. Analyzing this ever-increasing data presents several ch…
An Innovative Information Theory-based Approach to Tackle and Enhance The Transparency in Phishing Detection
Van Nguyen, Tingmin Wu, Xingliang Yuan +3
Phishing attacks have become a serious and challenging issue for detection, explanation, and defense. Despite more than a decade of research on phishing, encompassing both technica…