A Statistical Learning Based System for Fake Website Detection
This addresses the issue of ineffective fake website detection for users and organizations, but it appears incremental as it applies known methods to a specific domain.
The paper tackled the problem of fake website detection by developing a system based on statistical learning theory, which outperformed seven existing systems on a test bed of 900 websites.
Existing fake website detection systems are unable to effectively detect fake websites. In this study, we advocate the development of fake website detection systems that employ classification methods grounded in statistical learning theory (SLT). Experimental results reveal that a prototype system developed using SLT-based methods outperforms seven existing fake website detection systems on a test bed encompassing 900 real and fake websites.