Poster: User-Centric Phishing Threat Detection

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Provided by: National Taiwan Normal University
Topic: Security
Format: PDF
In this paper, the authors propose a user-centric model that exploits users' browsing behaviors only for context-aware phishing threat detection. Experimental results show that the authors' behavioral MEMM model, which explores browsing contexts of users' previous accesses, yield favorable results in the large-scale experiments. In practice, their cost-effective approach is a lightweight process compared to the existing content-based analysis for blocking phishing threats. This paper is their first exploration to adopt URL information alone for anti-phishing. More discriminative features from users' behavioral perspectives will be investigated in the future to further improve real-time filtering performance.
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