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    政大機構典藏 > 教育學院 > 教育學系 > 期刊論文 >  Item 140.119/67034
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/67034

    Title: An efficient two-phase spam filtering method based on e-mails categorization
    Authors: 許志堅
    Sheu, Jyh-Jian
    Contributors: 傳播學院
    Keywords: Data mining;decision tree;security;spam filtering
    Date: 2009.05
    Issue Date: 2014-06-30 18:06:19 (UTC+8)
    Abstract: 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.
    Relation: International Journal of Network Security, 8(3), 334-343
    Data Type: article
    Appears in Collections:[教育學系] 期刊論文

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