Personalized E-mail Filtering System Based on Usage Control
Changda Wang, Tingting Gong, Patricia Ghann · Journal of Software · 2013
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 e-mail 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.