This paper discusses a combined and platform-independent solution to detect websites that fake their identity. The approach combines white-listing, black-listing and heuristic strategies to provide an optimal phishing detection ratio against these so-called phishing websites while at the same time making sure that the number of wrongly classified legitimate websites remains as low as possible. For the implementation, a prototype solution was written in platform-independent Java. Practical challenges during the implementation as well as first practical results will be discussed. / A Thesis submitted to the Department of Computer Science in partial fulfillment of
the requirements for the degree of Master of Science. / Degree Awarded: Spring Semester, 2009. / Date of Defense: April 7, 2009. / Wolff, Heuristics, Phishing, Antiphishing, Security, It-Security, Internet, Computer Science / Includes bibliographical references. / Sudhir Aggarwal, Professor Directing Thesis; Zhenghai Duan, Committee Member; Zhenghao Zhang, Committee Member.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_169057 |
| Contributors | Wolff, Marcus (authoraut), Aggarwal, Sudhir (professor directing thesis), Duan, Zhenghai (committee member), Zhang, Zhenghao (committee member), Department of Computer Science (degree granting department), Florida State University (degree granting institution) |
| Publisher | Florida State University |
| Source Sets | Florida State University |
| Language | English, English |
| Detected Language | English |
| Type | Text, text |
| Format | 1 online resource, computer, application/pdf |
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