New anti-spam filter based on data mining and analysis of email security
Yu Chuan Wu, Zhijun Li, Ping Luo, Guoyin Wang · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2003
One main technical means of anti-Spam is to build filters in email transfer route. However, the design of many junk mail filters hasn't made use of the whole security information in an email, which exists mostly in mail header rather than in the text and accessory. In this paper, data mining based on rough sets is introduced to design a new anti-Spam filter. Firstly, by recording and analyzing the header of every collected email sample, we get all necessary original raw data. Next, by selecting and computing features from the original header data, we obtain our decision table including several condition attributes and one decision attribute. Then, a data mining technique based on rough sets, which mainly includes relative reduction and rule generation, is introduced to mine this decision table. And we obtain some useful anti-Spam knowledge from all the email headers. Finally, we have made tests by using our rules to judge different mails. Tests demonstrate that when mining on selected baleful email corpus with specific Spam rate, our anti-Spam filter has high efficiency and high identification rate. By mining email headers, we can find potential security problems of some email systems and cheating methods of Spam senders.