Keui-Ching Lee

• Software Engineer at Rakuten

This paper presents a context-aware phishing threat detection model from users’ behavioral perspectives. The context of users’ information accesses is investigated to explore the users’ browsing behaviors that confront phishing situations. Large-scale experiments show that our approach achieves an accuracy of 0.9973 and an F1 score of 0.9311 for pr...

This paper studies the feasibility of an early warning system that prevents users from the dangerous situations they may fall into during web surfing. Our approach adopts behavioral Hidden Markov Models to explore collective intelligence embedded in users' browsing behaviors for context-aware category prediction, and applies the results to web secu...