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Serial and Parallel Bayesian Spam Filtering using Aho-Corasick and PFAC

by Saima Haseeb, Mahak Motwani, Amit Saxena
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 74 - Number 17
Year of Publication: 2013
Authors: Saima Haseeb, Mahak Motwani, Amit Saxena
10.5120/12975-9567

Saima Haseeb, Mahak Motwani, Amit Saxena . Serial and Parallel Bayesian Spam Filtering using Aho-Corasick and PFAC. International Journal of Computer Applications. 74, 17 ( July 2013), 9-14. DOI=10.5120/12975-9567

@article{ 10.5120/12975-9567,
author = { Saima Haseeb, Mahak Motwani, Amit Saxena },
title = { Serial and Parallel Bayesian Spam Filtering using Aho-Corasick and PFAC },
journal = { International Journal of Computer Applications },
issue_date = { July 2013 },
volume = { 74 },
number = { 17 },
month = { July },
year = { 2013 },
issn = { 0975-8887 },
pages = { 9-14 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume74/number17/12975-9567/ },
doi = { 10.5120/12975-9567 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:42:59.799815+05:30
%A Saima Haseeb
%A Mahak Motwani
%A Amit Saxena
%T Serial and Parallel Bayesian Spam Filtering using Aho-Corasick and PFAC
%J International Journal of Computer Applications
%@ 0975-8887
%V 74
%N 17
%P 9-14
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

With the rapid growth of Internet, E-mail, with its convenient and efficient characteristics, has become an important means of communication in people's life. It reduces the cost of communication. It comes with Spam. Spam emails, also known as 'junk e-mails', are unsolicited one's sent in bulk with hidden or forged identity of the sender, address, and header information. It is vital to pursue more effective spam filtering approaches to maintain normal operations of e-mail systems and to protect the interests of email users. In this paper we developed a Spam filter based on Bayesian filtering method using Aho-corasick and PFAC string matching algorithm. This filter developed an improved version of spam filter based on traditional Bayesian spam filtering to improve spam filtering efficiency, and to reduce chances of misjudgement of malignant spam. For further improvement of Spam filtering process we are transform the filter in to parallel spam filter on GPGPU's by using PFAC Algorithm.

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Index Terms

Computer Science
Information Sciences

Keywords

Spam Filter Bayesian Spam Filter Aho-Corasick PFAC