Earticle

초록

영어

This paper analyses several common algorithms for spam filtering and shows the advantages and disadvantages of these algorithms for spam filtering. Each algorithm is only suitable for filtering specific spam. Some algorithms are suitable for Chinese, and some algorithms perform well in English. In a lot of spam, it is not reliable and inefficiency to using a single algorithm to separate out spam. Thereby, in order to improve the accuracy and efficiency of spam filtering, composite intelligent algorithm, which integrates and improves the existing algorithms by utilizing the advantages of previous algorithms and avoiding their shortages, is proposed. Moreover, an intelligent method that it has the ability of self-learning by using the contents of the e-mails is introduced. Finally, the outcome of experiment shows that the intelligent method achieves a better efficiency and performance.

목차

Abstract
 1. Introduction
 2. Contrast of Common Filtering Algorithm
  2.1. Filtering Algorithm via Rule Configuration
  2.2. Blacklisting Method
  2.3. A Intellectual Learning Method Based on the Statistical Theory
  2.4. An Intelligent Algorithm Based on Vector Space
  2.5. Remains Issue
 3. The Design of Composite Intelligent Algorithm
  3.1 Mail Filter Function
  3.2. E-mail Configuration
  3.3. Intelligent Learning Functions
  3.4. Feature Items Selection in Vocabulary
 4. Experimental Evaluations
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Jun Liu [ College of Computer Science, Chongqing University, Chongqing, China ]
• Shuyu Chen [ College of Software Engineering, Chongqing University, Chongqing, China ]
• Kai Liu [ College of Computer Science, Chongqing University, Chongqing, China ]
• Yong Zhou [ College of Computer Science, Chongqing University, Chongqing, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Security and Its Applications

• 간기

  격월간

• pISSN

  1738-9976

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605