5 papers
Bridging the Closed-World Gap: Interpretable Anomaly Detection via a Hybrid TSK-FCM Ensemble on the BETH Dataset
Lohith Srikanth Pentapalli, Josette Riep, Justin Ouwerkerk +1
A fundamental paradox plagues the deployment of Machine Learning in cybersecurity: supervised models generalize poorly to novel, Out-of-Distribution (OoD) attacks, whereas unsuperv…
Detecting Jailbreak Attempts in Clinical Training LLMs Through Automated Linguistic Feature Extraction
Tri Nguyen, Huy Hoang Bao Le, Lohith Srikanth Pentapalli +2
Detecting jailbreak attempts in clinical training large language models (LLMs) requires accurate modeling of linguistic deviations that signal unsafe or off-task user behavior. Pri…
A Gradient-Optimized TSK Fuzzy Framework for Explainable Phishing Detection
Lohith Srikanth Pentapalli, Jon Salisbury, Josette Riep +1
Phishing attacks represent an increasingly sophisticated and pervasive threat to individuals and organizations, causing significant financial losses, identity theft, and severe dam…
Jailbreak Detection in Clinical Training LLMs Using Feature-Based Predictive Models
Tri Nguyen, Lohith Srikanth Pentapalli, Magnus Sieverding +11
Jailbreaking in Large Language Models (LLMs) threatens their safe use in sensitive domains like education by allowing users to bypass ethical safeguards. This study focuses on dete…
Fuzzy Logic -- Based Scheduling System for Part-Time Workforce
Tri Nguyen, Kelly Cohen
This paper explores the application of genetic fuzzy systems to efficiently generate schedules for a team of part-time student workers at a university. Given the preferred number o…