Cantina: a content-based approach to detecting phishing web sites

  • Authors:
  • Yue Zhang;Jason I. Hong;Lorrie F. Cranor

  • Affiliations:
  • University of Pittsburgh;Carnegie Mellon University;Carnegie Mellon University

  • Venue:
  • Proceedings of the 16th international conference on World Wide Web
  • Year:
  • 2007

Quantified Score

Hi-index 0.02

Visualization

Abstract

Phishing is a significant problem involving fraudulent email and web sites that trick unsuspecting users into revealing private information. In this paper, we present the design, implementation, and evaluation of CANTINA, a novel, content-based approach to detecting phishing web sites, based on the TF-IDF information retrieval algorithm. We also discuss the design and evaluation of several heuristics we developed to reduce false positives. Our experiments show that CANTINA is good at detecting phishing sites, correctly labeling approximately 95% of phishing sites.