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A Comparison of Tools for Detecting Fake Websites
October 2009 (vol. 42 no. 10)
pp. 78-86
Ahmed Abbasi, University of Wisconsin-Milwaukee
Hsinchun Chen, University of Arizona
As fake website developers become more innovative, so too must the tools used to protect Internet users. A proposed system combines a support vector machine classifier and a rich feature set derived from website text, linkage, and images to better detect fraudulent sites.

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Index Terms:
machine learning, artificial Intelligence, computing methodologies, Web text analysis, natural language processing, computer systems organization
Citation:
Ahmed Abbasi, Hsinchun Chen, "A Comparison of Tools for Detecting Fake Websites," Computer, vol. 42, no. 10, pp. 78-86, Oct. 2009, doi:10.1109/MC.2009.306
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