An Alliance-Based Anti-spam Approach

The growing problem of spam mails has generated a need for reliable anti-spam filters. Much work has been done to improve specific algorithms for the task of detecting spam, but less work has been report on leveraging multiple algorithms in spam mails analysis. We presents an alliance-based approach to classify, discovery and exchange interesting information on spam mails. The spam filter is built based on the mixture of rough set theory, genetic algorithm and XCS classifier system. The filtering results of spam mails by alliance-based approach are evaluated with several metrics, the performance is great. Two main conclusions can be drawn from this paper: (1). The rules exchanged from other mail servers indeed help the spam filter blocking more spam mails than before. (2). A combination of several algorithms improves accuracy and reduces false positives for the problem of spam detection.