Content filtering for SMS systems based on Bayesian classifier and word grouping

Author

Belém, Dirceu ; Duarte-Figueiredo, Fátima

Author_Institution

Comput. Sci. Dept., Pontifical Catholic Univ. of Minas Gerais (PUC Minas), Belo Horizonte, Brazil

fYear

2011

fDate

10-11 Oct. 2011

Firstpage

1

Lastpage

7

Abstract

There are many researches about e-mail spam filters. However, only a few look at the issue for SMS (Short Message Service) systems. This is a result of the difficulty in having access to SMS platforms of mobile operators. Furthermore, the volume of spam to SMS systems has increased year after year. The main objective of this study is to propose the implementation of a content filter for SMS systems based on the Bayesian classifier and word grouping. In order to evaluate the performance of this filter, 120,000 messages, sent from a content provider that services mobile operators, were tested. The results demonstrated that the proposed filter reached correct spam index detection close to 100%.

Keywords

Bayes methods; electronic messaging; pattern classification; security of data; unsolicited e-mail; Bayesian classifier; SMS system; content filtering; e-mail spam filters; mobile operators; short message service systems; spam index detection; word grouping; Bayesian methods; Electronic mail; Filtering; Filtering algorithms; Mobile communication; Training; Bayesian; Classifier; Grouping Words; SMS Systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Network Operations and Management Symposium (LANOMS), 2011 7th Latin American

Conference_Location

Quito

Print_ISBN

978-1-4577-1790-1

Type

conf

DOI

10.1109/LANOMS.2011.6102272

Filename

6102272