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題名 An intelligent three‐phase spam filtering method based on decision tree data mining
作者 許志堅
貢獻者 傳播學院
關鍵詞 spam; data mining; decision tree
日期 2016-11
上傳時間 19-六月-2018 15:27:23 (UTC+8)
摘要 In this paper, we proposed an efficient spamfiltering method based on decision tree data mining technique, analyzed the as-sociation rules about spams, and applied these rules to develop a systematized spamfiltering method. Our method possessedthe following three major superiorities: (i) checking only an e-mail’s header section to avoid the low-operating efficiency inscanning an e-mail’s content. Moreover, the accuracy offiltering was enhanced simultaneously. (ii) In order that the probablemisjudgment in identifying an unknown e-mail could be“reversed”, we had constructed a reversing mechanism to help theclassification of unknown e-mails. Thus, the overall accuracy of ourfiltering method will be increased. (iii) Our method wasequipped with a re-learning mechanism, which utilized the supervised machine learning method to collect and analyze eachmisjudged e-mail. Therefore, the revision information learned from the analysis of misjudged e-mails incrementally gavefeedback to our method, and its ability of identifying spams would be improved.
關聯 Security and Communication Networks 【SCI-E】, Vol.9, No.17, pp.4013-4026
資料類型 article
dc.contributor 傳播學院zh_TW
dc.creator (作者) 許志堅zh_TW
dc.date (日期) 2016-11
dc.date.accessioned 19-六月-2018 15:27:23 (UTC+8)-
dc.date.available 19-六月-2018 15:27:23 (UTC+8)-
dc.date.issued (上傳時間) 19-六月-2018 15:27:23 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/117811-
dc.description.abstract (摘要) In this paper, we proposed an efficient spamfiltering method based on decision tree data mining technique, analyzed the as-sociation rules about spams, and applied these rules to develop a systematized spamfiltering method. Our method possessedthe following three major superiorities: (i) checking only an e-mail’s header section to avoid the low-operating efficiency inscanning an e-mail’s content. Moreover, the accuracy offiltering was enhanced simultaneously. (ii) In order that the probablemisjudgment in identifying an unknown e-mail could be“reversed”, we had constructed a reversing mechanism to help theclassification of unknown e-mails. Thus, the overall accuracy of ourfiltering method will be increased. (iii) Our method wasequipped with a re-learning mechanism, which utilized the supervised machine learning method to collect and analyze eachmisjudged e-mail. Therefore, the revision information learned from the analysis of misjudged e-mails incrementally gavefeedback to our method, and its ability of identifying spams would be improved.en_US
dc.format.extent 933977 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) Security and Communication Networks 【SCI-E】, Vol.9, No.17, pp.4013-4026zh_TW
dc.subject (關鍵詞) spam; data mining; decision treeen_US
dc.title (題名) An intelligent three‐phase spam filtering method based on decision tree data miningen_US
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.1002/sec.1584