Off-the-Hook: An Efficient and Usable Client-Side Phishing Prevention Application

S. Marchal, G. Armano, T. Gröndahl, Kalle Saari, Nidhi Singh, N. Asokan

Research output: Contribution to journalArticleScientificpeer-review

54 Citations (Scopus)


Phishing is a major problem on the Web. Despite the significant attention it has received over the years, there has been no definitive solution. While the state-of-the-art solutions have reasonably good performance, they suffer from several drawbacks including potential to compromise user privacy, difficulty of detecting phishing websites whose content change dynamically, and reliance on features that are too dependent on the training data. To address these limitations we present a new approach for detecting phishing webpages in real-time as they are visited by a browser. It relies on modeling inherent phisher limitations stemming from the constraints they face while building a webpage. Consequently, the implementation of our approach, Off-the-Hook, exhibits several notable properties including high accuracy, brand-independence and good language-independence, speed of decision, resilience to dynamic phish and resilience to evolution in phishing techniques. Off-the-Hook is implemented as a fully-client-side browser add-on, which preserves user privacy. In addition, Off-the-Hook identifies the target website that a phishing webpage is attempting to mimic and includes this target in its warning. We evaluated Off-the-Hook in two different user studies. Our results show that users prefer Off-the-Hook warnings to Firefox warnings.
Original languageEnglish
Pages (from-to)1717-1733
Number of pages17
JournalIEEE Transactions on Computers
Issue number10
Publication statusPublished - 1 Oct 2017
MoE publication typeA1 Journal article-refereed


  • Browsers
  • Detectors
  • Electronic mail
  • Feature extraction
  • Privacy
  • Real-time systems
  • Uniform resource locators
  • Phishing webpage detection
  • browser add-on
  • machine learning
  • phishing prevention
  • phishing target identification
  • web security


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