| Summary: | 碩士 === 國立臺灣科技大學 === 資訊工程系 === 92 === The two mainly goals in the system are filtering spam E-mails and stopping those malevolence programs, such as virus, backdoor and Trojan Horse, to send E-mails through user’s Mail User Agent. The most important key points of a perfect spam filtering system include high speed and correctness when classifying between spam and legitimate E-mails, and SSVM is one of the most suitable machine algorithms in classifying. In this system we use two public standard training and testing data set: Ling-Spam corpus and PU1 corpus. Each data in these two corpus set will translate from textual form into vector form, and each vector has 108 feature columns. Using these vector-form data, we can use SSVM to train and test our optimal classifying function. From the results of experiments in this paper, we can get totally better Spam Precision and Spam Recall values than other researches before.
Besides, our system will also install a firewall in user’s personal computer to stop malevolence programs sending E-mails. The firewall will guard user’s port 25 in order to stop those malevolence programs fake as normal TCP/IP packets but send E-mails stealthily.
Based on these two important parts, this system can help users build a clear, safely, and non-spam network environment.
|
|---|
