The effects of spam on network is discussed. Unsolicited messages or spam, flood our email boxes, viruses, worms, and denial-of service attacks that cripple computer networks may secret in spam. This threaten network security, stability and reliability seriously. In this paper, A new scheme based on decision-theoretic rough sets is introduced to classify emails into three categories -spam, no-spam and suspicious. By comparing with popular classification methods like Naive Bayes classification, our anti-Spam filter model reduce the error ratio that a non-spam is discriminated to spam, and we can find potential security problems of some email systems.
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