SpamTerminator: A Personal Anti-spam Add-In for Outlook

Authors:
Wenbin Li;Yiying Cheng;Ning Zhong;Taifeng Liu;Xindong Zhang
Affiliations:
Shijiazhuang University of Economics, Shijiazhuang, China 050031 and Beijing University of Technology, Beijing, China 100022 and Hebei Normal University, Shijiazhuang, China 050000;Shijiazhuang University of Economics, Shijiazhuang, China 050031;Beijing University of Technology, Beijing, China 100022 and Dept. of Information Engineering, Maebashi Institute of Technology, Maebashi-City, Japan 371-0816;Shijiazhuang University of Economics, Shijiazhuang, China 050031;Shijiazhuang University of Economics, Shijiazhuang, China 050031
Venue:
AMT '09 Proceedings of the 5th International Conference on Active Media Technology
Year:
2009

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Abstract

Spam filtering has witnessed a booming interest in the recent years, due to the increased abuse of email. This paper presents SpamTerminator, a personal anti-spam filtering add-in of Outlook. Outstanding characteristics of SpamTerminator are as follows. First, it provides eleven filters including rule-based, white lists, black lists, four single filters, and four ensemble filters. As a result, SpamTerminator can automatically work for users in different stages even if they do not train machine learning-based filters. Secondly, by using our proposed method named TPL (Two-Phases Learning) to combine multiple disparate classifiers, ensemble filters can achieve excellent discrimination between spam and legitimate mail.