Title :
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
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;
Conference_Titel :
Network Operations and Management Symposium (LANOMS), 2011 7th Latin American
Conference_Location :
Quito
Print_ISBN :
978-1-4577-1790-1
DOI :
10.1109/LANOMS.2011.6102272
