Soft Computing

, Volume 11, Issue 8, pp 729–740 | Cite as

Artificial immune system inspired behavior-based anti-spam filter

  • Xun Yue
  • Ajith Abraham
  • Zhong-Xian Chi
  • Yan-You Hao
  • Hongwei Mo


This paper proposes a novel behavior-based anti-spam technology for email service based on an artificial immune-inspired clustering algorithm. The suggested method is capable of continuously delivering the most relevant spam emails from the collection of all spam emails that are reported by the members of the network. Mail servers could implement the anti-spam technology by using the “black lists” that have been already recognized. Two main concepts are introduced, which defines the behavior-based characteristics of spam and to continuously identify the similar groups of spam when processing the spam streams. Experiment results using real-world datasets reveal that the proposed technology is reliable, efficient and scalable. Since no single technology can achieve one hundred percent spam detection with zero false positives, the proposed method may be used in conjunction with other filtering systems to minimize errors.


Spam Clustering algorithm Artificial immune system Artificial immune network 


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Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • Xun Yue
    • 1
    • 2
  • Ajith Abraham
    • 3
  • Zhong-Xian Chi
    • 1
  • Yan-You Hao
    • 1
  • Hongwei Mo
    • 4
  1. 1.Department of Computer Science and EngineeringDalian University of TechnologyDalianChina
  2. 2.College of Information Sciences and EngineeringShandong Agricultural UniversityTaianChina
  3. 3.IITA Professorship Program, School of Computer Science and EngineeringChung-Ang UniversityDongjak-gu SeoulRepublic of Korea
  4. 4.Automation CollegeHarbin Engineering UniversityHarbinChina

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