Please use this identifier to cite or link to this item:
https://ah.lib.nccu.edu.tw/handle/140.119/67034
題名: | An efficient two-phase spam filtering method based on e-mails categorization | 作者: | 許志堅 Sheu, Jyh-Jian |
貢獻者: | 傳播學院 | 關鍵詞: | Data mining; decision tree; security; spam filtering | 日期: | 2009 | 上傳時間: | 30-Jun-2014 | 摘要: | The e-mail`s header session usually contains important attributes such as e-mail title, sender`s name, sender`s e-mail address, sending date, which are helpful to classication of e-mails. In this paper, we apply decision tree data mining technique to header`s basic attributes to analyze the association rules of spam e-mails and propose an efficient spam ¯ltering method to accurately identify spam and legitimate e-mails. According to the experiment of applying numerous Chinese e-mails to our spam ¯ltering method, we obtain the following excellent datums: the Accuracy is 96.5%, the Precision is 96.67%, and the Re-call is 96.3%. Thus, the method proposed in this paper can e±ciently identify the spam e-mails by checking only the header sessions, which can reduce the cost for calculation. | 關聯: | International Journal of Network Security, 8(3), 334-343 | 資料類型: | article |
Appears in Collections: | 期刊論文 |
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File | Description | Size | Format | |
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334-343.pdf | 185.92 kB | Adobe PDF2 | View/Open |
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