A Method for Spam Behavior Recognition Based on Fuzzy Decision Tree

Behavior recognition technology can determine whether an email is a spam or ham based on behavior features instead of contents. Statistical behavior features are high degree distinct between spam and ham, and comparatively inherent. This paper proposed a spam behavior recognition model, and developed a Fuzzy Decision Tree based spam filter system. The system computed Information Gain to analyze and select behavior features of emails. The absolutely clear attributes does not always exist in real world. Email features extracted from email messages, and processed by fuzzy processor and data generalization, and more natural and reasonable to describe the characteristics of behavior. According to knowledge of the fuzzy decision tree by Fuzzy-ID3, spam can be detected and classified spam sender behavior patterns can by analyzed automatically.