Leveraging Website Genre and Structure Information for Fake Website Detection
نویسنده
چکیده
In this study we assessed the efficacy of using website genre composition and design structure information for fake website detection. A genre tree kernel was proposed that creates a rooted tree from the website file directory structure, and labels the tree’s file nodes with genre information. The genre tree kernel was compared against several benchmark kernel and non-kernel methods that utilized a rich feature set comprised of thousands of website content-based attributes. Experimental results revealed that the genre tree kernel outperformed all comparison methods on a test bed encompassing 900 legitimate, concocted and spoof sites. The results suggest that fake website detection systems could benefit from the use of genre and design structure information.
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