JSW 2013 Vol.8(4): 860-867 ISSN: 1796-217X
doi: 10.4304/jsw.8.4.860-867
doi: 10.4304/jsw.8.4.860-867
Personalized E-mail Filtering System Based on Usage Control
Changda Wang, Tingting Gong, Patricia Ghann
School of Computer Science and Telecommunication Engineering, Jiangsu University, Zhenjiang, China
Abstract—In order to cope with the problem of spam soaring, a personalized e-mail filtering method based on UCON is proposed. E-mails from different senders were classified as junk e-mail, suspicious e-mail and normal email by trust third-party according to the maintained blacklist and embedded machine learning technology online. Suspicious e-mails will be classified further from users’ point of view manually. Then the incoming e-mails would be sifted and processed differently according to their classification. Experiments results illustrate the method of the paper not only provide a personalization filtering but also more accurate and effective than the popular statistical spam filtering system.
Index Terms—Spam filtering, personalization filtering, usage control.
Abstract—In order to cope with the problem of spam soaring, a personalized e-mail filtering method based on UCON is proposed. E-mails from different senders were classified as junk e-mail, suspicious e-mail and normal email by trust third-party according to the maintained blacklist and embedded machine learning technology online. Suspicious e-mails will be classified further from users’ point of view manually. Then the incoming e-mails would be sifted and processed differently according to their classification. Experiments results illustrate the method of the paper not only provide a personalization filtering but also more accurate and effective than the popular statistical spam filtering system.
Index Terms—Spam filtering, personalization filtering, usage control.
Cite: Changda Wang, Tingting Gong, Patricia Ghann, "Personalized E-mail Filtering System Based on Usage Control," Journal of Software vol. 8, no. 4, pp. 860-867, 2013.
General Information
ISSN: 1796-217X (Online)
Frequency: Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKI, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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