Detecting fake escrow websites using rich fraud cues and kernel based methods

Ahmed Abbasi, Hsinchun Chen

Research output: Contribution to conferencePaper

5 Scopus citations

Abstract

The ability to automatically detect fraudulent escrow websites is important in order to alleviate online auction fraud. Despite research on related topics, fake escrow website categorization has received little attention. In this study we evaluated the effectiveness of various features and techniques for detecting fake escrow websites. Our analysis included a rich set of features extracted from web page text, image, and link information. We also proposed a composite kernel tailored to represent the properties of fake websites, including content duplication and structural attributes. Experiments were conducted to assess the proposed features, techniques, and kernels on a test bed encompassing nearly 90,000 web pages derived from 410 legitimate and fake escrow sites. The combination of an extended feature set and the composite kernel attained over 98% accuracy when differentiating fake sites from real ones, using the support vector machines algorithm. The results suggest that automated web-based information systems for detecting fake escrow sites could be feasible and may be utilized as authentication mechanisms.

Original languageEnglish (US)
Pages55-60
Number of pages6
StatePublished - Jan 1 2007
Event17th Workshop on Information Technologies and Systems, WITS 2007 - Montreal, QC, Canada
Duration: Dec 8 2007Dec 9 2007

Other

Other17th Workshop on Information Technologies and Systems, WITS 2007
CountryCanada
CityMontreal, QC
Period12/8/0712/9/07

Keywords

  • Internet fraud
  • Kernel-based methods
  • Online escrow services
  • Website classification

ASJC Scopus subject areas

  • Information Systems

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