MVGL analyser for multi-classifier based spam filtering system

MD Rafiqul Islam, Wanlei Zhou, Morshed U. Chowdhury

Research output: Book chapter/Published conference paperConference paperpeer-review

1 Citation (Scopus)


In the last decade, the rapid growth of the Internet and email, there has been a dramatic growth in spam. Spam is commonly defined as unsolicited email messages and protecting email from the infiltration of spam is an important research issue. Classifications algorithms have been successfully used to filter spam, but with a certain amount of false positive trade-offs, which is unacceptable to users sometimes. This paper presents an approach to overcome the burden of GL (grey list) analyzer as further refinements to our multi-classifier based classification model (Islam, M. and W. Zhou 2007). In this approach, we introduce a ldquomajority voting grey list (MVGL)rdquo analyzing technique which will analyze the generated GL emails by using the majority voting (MV) algorithm. We have presented two different variations of the MV system, one is simple MV (SMV) and other is the ranked MV (RMV). Our empirical evidence proofs the improvements of this approach compared to the existing GL analyzer of multi-classifier based spam filtering process.
Original languageEnglish
Title of host publicationIEEE/ACIS 2009
Place of PublicationUnited States
PublisherInstitute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)9780769536415
Publication statusPublished - 2009
EventIEEE/ACIS International Conference on Computer and Information Science - Shanghai, China, China
Duration: 01 Jun 200903 Jun 2009


ConferenceIEEE/ACIS International Conference on Computer and Information Science


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