Please use this identifier to cite or link to this item:
https://ah.lib.nccu.edu.tw/handle/140.119/67034
DC Field | Value | Language |
---|---|---|
dc.contributor | 傳播學院 | en_US |
dc.creator | 許志堅 | zh_TW |
dc.creator | Sheu, Jyh-Jian | en_US |
dc.date | 2009.05 | en_US |
dc.date.accessioned | 2014-06-30T10:06:19Z | - |
dc.date.available | 2014-06-30T10:06:19Z | - |
dc.date.issued | 2014-06-30T10:06:19Z | - |
dc.identifier.uri | http://nccur.lib.nccu.edu.tw/handle/140.119/67034 | - |
dc.description.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. | en_US |
dc.format.extent | 190381 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | en_US | - |
dc.relation | International Journal of Network Security, 8(3), 334-343 | en_US |
dc.subject | Data mining; decision tree; security; spam filtering | en_US |
dc.title | An efficient two-phase spam filtering method based on e-mails categorization | en_US |
dc.type | article | en |
item.grantfulltext | restricted | - |
item.openairetype | article | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.languageiso639-1 | en_US | - |
item.cerifentitytype | Publications | - |
item.fulltext | With Fulltext | - |
Appears in Collections: | 期刊論文 |
Files in This Item:
File | Description | Size | Format | |
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334-343.pdf | 185.92 kB | Adobe PDF2 | View/Open |
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