FAKE WEBSITE DETECTION USING SUPPORT VECTOR MACHINE LINEAR
The trends of cybercrime through fake website make people try to design fake website detection system. Using a Statistical Learning Theory, we propose a mathematical model for detecting fake websites based on Plug-in Classier with Bayesian Statistics and Support Vector Machine Linear methods. Thi...
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| Main Author: | |
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| Format: | Theses |
| Language: | Indonesia |
| Subjects: | |
| Online Access: | https://digilib.itb.ac.id/gdl/view/33867 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | The trends of cybercrime through fake website make people try to design fake
website detection system. Using a Statistical Learning Theory, we propose
a mathematical model for detecting fake websites based on Plug-in Classier
with Bayesian Statistics and Support Vector Machine Linear methods. This
research uses fraud cue as training data which consist of internal links, webpage
levels, and screenshoot of webpage header. These two methods applied
to detect a number of legitimate and fake websites. The result shows that the
Support Vector Machine Linear model has better website detection than the
Plug-in Classier model. |
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