Research on the Comprehensive Anti-Spam Filter

Unsolicited bulk email (aka. spam) is a major problem on the Internet. To counter spam, several techniques, ranging from spam filters to mail protocol extensions have been proposed. In this paper we investigate the effectiveness of several spam filtering techniques and technologies, present an anti-spam filter that integrates the main empirical conclusions of our comprehensive analysis on anti-spam filters. We assess its behavior in real use and the results are deemed satisfactory.

[1]  Virgílio A. F. Almeida,et al.  Characterizing a spam traffic , 2004, IMC '04.

[2]  Catherine Rosenberg,et al.  Behavioral authentication of server flows , 2003, 19th Annual Computer Security Applications Conference, 2003. Proceedings..

[3]  Harris Drucker,et al.  Support vector machines for spam categorization , 1999, IEEE Trans. Neural Networks.

[4]  J. Ross Quinlan,et al.  C4.5: Programs for Machine Learning , 1992 .

[5]  Susan T. Dumais,et al.  A Bayesian Approach to Filtering Junk E-Mail , 1998, AAAI 1998.

[6]  José María Gómez Hidalgo,et al.  Combining Text and Heuristics for Cost-Sensitive Spam Filtering , 2000, CoNLL/LLL.

[7]  Fabrizio Sebastiani,et al.  Machine learning in automated text categorization , 2001, CSUR.