E-mail worm detection using the analysis of behavior

Authors:
Tao Jiang;Wonil Kim;Kyungsuk Lhee;Manpyo Hong
Affiliations:
Digital Vaccine and Internet Immune System Laboratory, Graduate School of Information and Communication, Ajou University, Suwon, Korea;College of Electronics and Information Engineering, Sejong University, Seoul, Korea;Digital Vaccine and Internet Immune System Laboratory, Graduate School of Information and Communication, Ajou University, Suwon, Korea;Digital Vaccine and Internet Immune System Laboratory, Graduate School of Information and Communication, Ajou University, Suwon, Korea
Venue:
ICDCIT'05 Proceedings of the Second international conference on Distributed Computing and Internet Technology
Year:
2005

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Abstract

With the appearance of a number of e-mail worms in recent years, we urgently need a solution to detect unknown e-mail worms rather than using the traditional solution: signature-based scanning which does not deal with the new e-mail worms well. Our collected data shows that the quantitative trend of e-mail worms is really exploding. In this paper, we propose an e-mail worm Detection System that is based on analysis on human and worm behavior for detecting unknown e-mail worms. Message data such as e-mail or short messages are the result of human behavior. The proposed system detects unknown worms by assessment of behavior in communication because human behavior and worm behavior have different projection on data.