Application of sim-hash algorithm and big data analysis in spam email detection system

Abstract

Currently, there are many effective techniques that are used for filtering spam emails. However, spammers have mostly identified the weakness of those methods in order to bypass current detection systems. In this paper, we propose a novel similarity-based method that implements the fingerprinting technique on parallel processing framework. Furthermore, meet-in-the-middle approach is used in our method to achieve a higher accuracy in the spam email detection system. Our experimental result demonstrates the improved efficiency of this study.