• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

The Adaptive SPAM Mail Detection System using Clustering based on Text Mining

Vol. 8, No.6, June 27, 2014
10.3837/tiis.2014.06.022, Download Paper (Free):

Abstract

Spam mail is one of the most general mail dysfunctions, which may cause psychological damage to internet users. As internet usage increases, the amount of spam mail has also gradually increased. Indiscriminate sending, in particular, occurs when spam mail is sent using smart phones or tablets connected to wireless networks. Spam mail consists of approximately 68% of mail traffic; however, it is believed that the true percentage of spam mail is at a much more severe level. In order to analyze and detect spam mail, we introduce a technique based on spam mail characteristics and text mining; in particular, spam mail is detected by extracting the linguistic analysis and language processing. Existing spam mail is analyzed, and hidden spam signatures are extracted using text clustering. Our proposed method utilizes a text mining system to improve the detection and error detection rates for existing spam mail and to respond to new spam mail types.


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Cite this article

[IEEE Style]
Sung-Sam Hong, Jong-Hwan Kong and Myung-Mook Han, "The Adaptive SPAM Mail Detection System using Clustering based on Text Mining," KSII Transactions on Internet and Information Systems, vol. 8, no. 6, pp. 2186-2196, 2014. DOI: 10.3837/tiis.2014.06.022

[ACM Style]
Hong, S., Kong, J., and Han, M. 2014. The Adaptive SPAM Mail Detection System using Clustering based on Text Mining. KSII Transactions on Internet and Information Systems, 8, 6, (2014), 2186-2196. DOI: 10.3837/tiis.2014.06.022