Home // ICCGI 2011, The Sixth International Multi-Conference on Computing in the Global Information Technology // View article

A Hybrid and Auto-adjusted Spam Filter

Authors:
Shu Bin Chen
Hsiao Ping Lee
Tzu-Fang Sheu

Keywords: spam; list-based method; behavior-based filter; content; Internet.

Abstract:
The spam E-mail problem has become more and more serious today. Enterprises and users have to spend lots of time on filtering out useful messages from spam. A variety of spam filtering mechanisms had been proposed, including list-based method, behavior-based filter, content-based method, and cocktail filtering mechanisms. In order to improve the accuracy of spam filters, this paper proposes a novel spam detection system, which combines a behavior-based method and a blacklist method. The proposed system will analyze spam behaviors and then generate behavior patterns. Additionally, the propose system will use an auto-updated blacklist mechanism which collects the updates from anti-spam organizations. The proposed system also uses a feedback mechanism that adjusts the behavior patterns based on users’ responses. Therefore, the proposed spam detection system can perform more efficiently and accurately.

Pages: 177 to 180

Copyright: Copyright (c) IARIA, 2011

Publication date: June 19, 2011

Published in: conference

ISSN: 2308-4529

ISBN: 978-1-61208-139-7

Location: Luxembourg City, Luxembourg

Dates: from June 19, 2011 to June 24, 2011