Fuzzy Decision Tree Based Inference Technology for Spam Behavior Recognition

Abstract

Anti-spam technology has been developed to the third generation technology, behavior recognition technology. There are many traditional classification models, among which, decision tree model is the one most widely used, and has a good intelligibility. But the absolutely clear attributes does not always exist in real world. This paper proposed a fuzzy decision tree based method for spam behavior recognition. After preprocessing (data discretization, transformation and compression for continuous-value attributes), the attribute subordinating degree is 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.