A Surveillance Spyware Detection System Based on Data Mining Methods
| Autor: | Zi-Yan Wang, 王子彥 |
|---|---|
| Rok vydání: | 2005 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 93 Nowadays, the problem of spyware is incredibly serious; some famous anti-virus software vendors such as Norton, Trend Micro had entered the spyware -detection field last year. Even Microsoft and Yahoo also had thrown themselves into the battle of anti-spyware. But there are still less effort to understand it in the research community. At present, there is only one research [29] about the spyware in 2004. In this thesis, we proposed an integrated architecture to defend against surveillance spyware. For overcoming the lacks of usual anti-spyware products, we combine the methods of static analysis and dynamic analysis to extract feature of spyware. By adopting the concepts of machine learning and data-mining, we construct a spyware detection system (SDS) which has 98% detecting rate for known spyware and 96% detecting rate for unknown or novel spyware. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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