期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2017
卷号：6
期号：7
页码：14195
DOI：10.15680/IJIRSET.2017.0607214
出版社：S&S Publications
摘要：This paper presents a hybrid Bayesian algorithm using reliable swarm intelligence to recognize andblock SPAM emails. Due to low cost of communication & easily advertisement is possible with e-mails ,severalpeople & companies use it to quickly distribute unsolicited bulk messages ,also called spam, to a large number ofpeople in a very short time .Due to unnecessary traffic & security threats ,spam has become a major threat for not onlybusiness users to also network administrators & even to ordinary users. In addition to regulate, several technicalsolutions have been proposed and after a certain time it is found the content based on SPAM recognition is best suitedin it. By including Bayesian rule (Bay’s theorem) in content scanning, over all influence the popular e-mails forsuitable recognition of SPAM mails can be increased worldwide.But in this approach many limitations are proposed due to static values of probabilities for each token. For overcomingthis limitation automated training is deployed for filtering purpose. for classifying and recognize the best tokens inSPAM can make more strong automated trained filter by including in it nature based optimization techniques SMO(spider monkey optimization )are best suited for this and have include in this paper.
