papers

Publications (6)

cs.CR2026

A Survey of Heterogeneous Graph Neural Networks for Cybersecurity Anomaly Detection

Laura Jiang, Reza Ryan, Qian Li +1

Anomaly detection is a critical task in cybersecurity, where identifying insider threats, access violations, and coordinated attacks is essential for ensuring system resilience. Gr…

cs.CR2026

A Deterministic Forensic Preprocessing Framework for Heterogeneous Network Datasets: Formal Foundations, Implementation, and Empirical Validation

Ravi Chaudhary, Reza Ryan, Nasim Ferdosian +2

Digital forensic investigations increasingly depend on preprocessing heterogeneous network evidence from intrusion detection systems, IoT devices, and enterprise traffic logs. Inco…

cs.AI2026

From Minds to Models: The Intersection of Psychology and LLM Behaviours

Oliver Guidetti, Reza Ryan

The paper applies psychological methods, specifically a prompt-based Implicit Association Test, to examine whether ChatGPT exhibits sentiment differences across racial conditions,…

#large language models#bias evaluation#sentiment analysis#psychology methods
cs.CR2026

Rethinking Fraud Safety Evaluation: Multi-Round Attacks Reveal Safety-Utility Tradeoffs in Graph-Context LLM Defenders

Laura Jiang, Reza Ryan, Qian Li +1

Single-turn safety evaluation is a poor proxy for real fraud defense, where attackers escalate across multiple rounds. This paper evaluates fraud defenders under replay and adaptiv…

cs.CR2025

Smart Surveillance: Identifying IoT Device Behaviours using ML-Powered Traffic Analysis

Reza Ryan, Napoleon Paciente, Cahil Youngs +3

The proliferation of Internet of Things (IoT) devices has grown exponentially in recent years, introducing significant security challenges. Accurate identification of the types of…

cs.AI2025

LLMLogAnalyzer: A Clustering-Based Log Analysis Chatbot using Large Language Models

Peng Cai, Reza Ryan, Nickson M. Karie

System logs are a cornerstone of cybersecurity, supporting proactive breach prevention and post-incident investigations. However, analyzing vast amounts of diverse log data remains…