Abstract—Concerning the problem that a large number of
spam disturbing the user, a method named adaptive learning
algorithm was proposed. The passive attack method based on
the Simple Mail Transfer Protocol(SMTP) session log initiated
by the mail host in the campus during half a year. Analysis on
the status of delivery rate and many types of failure message of
the host behavior in the session record, and ultimately achieve
effective adaptation by detecting spam source host behavior on
the recent email classification. The experimental results show
that the implementation of a number of rounds of classification
strategy adjustment, at last the detection accuracy can reach
94.7%. The design is very useful for network administrators, he
can effectively detect spam internal host status, and control the
behavior of the spam host in the beginning.
Index Terms—Spam host, SMTP session, adaptive learning, categorizer, failure information.
The authors are with Nanjing Normal University, Jiangsu, China (e-mail:
60167@njnu.edu.cn).
[PDF]
Cite: Bin Chen, Yizhou Dong, and Mingrong Mao, "Mail Detection Model of Campus Network Based on the Adaptive Learning Algorithm," International Journal of Future Computer and Communication vol. 6, no. 2, pp. 63-66, 2017.
