Phishing Attack Simulation and Detection Strategies: A Case Study on NTNU Moodle Platform

With the development of the digital society, phishing attacks have become an increasingly serious cybersecurity threat, posing risks not only to general users but also serving as a common initial intrusion method in Advanced Persistent Threat (APT) attacks. In this study, we simulated a phishing attack targeting the Moodle system of National Taiwan Normal University and collected 104 valid survey responses to investigate phishing website recognition behaviors. The results indicate that checking the URL is one of the most effective methods for users to identify phishing websites. In the future, we plan to develop a browser extension integrated with Large Language Models (LLMs) to automatically detect high-risk phishing websites and provide real-time warnings to users, thereby enhancing overall protection capabilities.