An Intelligent SPAM filter - GetEmail5

Author

Hassan, Tarek ; Cole, Peter ; Fung, Chun Che

Author_Institution

Sch. of Inf. Technol., Murdoch Univ., WA

fYear

2006

fDate

7-9 June 2006

Firstpage

1

Lastpage

5

Abstract

As the increasing reliance on electronic mail (email) continues, unsolicited bulk email (SPAM) also continues to grow because it is a very cheap way for advertising. These unwanted emails are now causing a serious problem in clogging the Internet traffic and filling up the email inboxes thereby leaving no space for legitimate emails to pass through. In addition, dealing with SPAM messages is costly to the users as it requires time and effort to examine them individually. In this paper, we propose an intelligent and trainable SPAM filter called GetEmail5. We have also evaluated the proposed filter against two commercial filters, EmailProtect and SpamEater

Keywords

Bayes methods; information filters; unsolicited e-mail; Bayesian filter; GetEmail5; Internet traffic; black list filter; intelligent SPAM filter; unsolicited bulk email; unsolicited commercial email; white list filter; Business; Costs; Electronic mail; Filling; Information filtering; Information filters; Information technology; Internet; Postal services; Unsolicited electronic mail; Bayesian filter; SPAM filter; Unsolicited Bulk E-mail (UBE); Unsolicited Commercial E-mail (UCE); black list; white list;

fLanguage

English

Publisher

ieee

Conference_Titel

Cybernetics and Intelligent Systems, 2006 IEEE Conference on

Conference_Location

Bangkok

Print_ISBN

1-4244-0023-6

Type

conf

DOI

10.1109/ICCIS.2006.252253

Filename

4017812