DocumentCode :
3378476
Title :
An Email Classification Scheme Based on Decision-Theoretic Rough Set Theory and Analysis of Email Security
Author :
Zhao, Wenqing ; Zhu, Yongli
Author_Institution :
North China Electr. Power Univ., Beijing
fYear :
2005
fDate :
21-24 Nov. 2005
Firstpage :
1
Lastpage :
6
Abstract :
The effects of spam on network is discussed. Unsolicited messages or spam, flood our email boxes, viruses, worms, and denial-of service attacks that cripple computer networks may secret in spam. This threaten network security, stability and reliability seriously. In this paper, A new scheme based on decision-theoretic rough sets is introduced to classify emails into three categories - spam, no-spam and suspicious. By comparing with popular classification methods like Naive Bayes classification, our anti-Spam filter model reduce the error ratio that a non-spam is discriminated to spam, and we can find potential security problems of some email systems.
Keywords :
Bayes methods; classification; computer network reliability; computer viruses; decision theory; information filtering; information filters; rough set theory; unsolicited e-mail; Naive Bayes classification; antispam filter model; computer networks; computer viruses; decision-theoretic rough set theory; denial-of service attacks; email boxes; email classification scheme; email security analysis; network reliability; network security; network stability; unsolicited messages; worms; Computer network reliability; Filtering; Filters; Machine learning; Machine learning algorithms; Rough sets; Security; Set theory; Text categorization; Unsolicited electronic mail; filtering; message systems; networks; security;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
TENCON 2005 2005 IEEE Region 10
Conference_Location :
Melbourne, Qld.
Print_ISBN :
0-7803-9311-2
Electronic_ISBN :
0-7803-9312-0
Type :
conf
DOI :
10.1109/TENCON.2005.301121
Filename :
4085009
Link To Document :
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