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International Journal of New Technology and Research

Impact Factor 3.953

(An ISO 9001:2008 Certified Online Journal)
India | Germany | France | Japan

An Collaborative and Early Detection of Email Spam Using Multitask Learning

( Volume 7 Issue 4,April 2021 ) OPEN ACCESS

Hariharan N, Kamaraj G, Ramanuja Babu R D


Deep Neural Network, Convolution Neural Network, Botnets.


Currently, E-mail is one of the most important methods of communication. The increasing of spam e-mails causes traffic congestion, decreasing productivity, which has become a serious problem for our society. The problem of Email spam has grown significantly over the past few years. It is not just a nuisance for users but also it is damaging for those who fall for scams and other attacks.The complexity intensification of Email spamming techniques which are advancing from traditional spamming (direct spamming) techniques to a more scalable and indirect approach of botnets for distributing Email spam message is the major reason for it.The aim of this research is to find an effective solution to filter possible spam e-mails.In this paper a hybrid solution which uses machine learning algorithms like Deep Neural Network, Convolution Neural Network are used to produce an improved  result and efficiency compared to existing system.The experimental results show that the proposed algorithm has 92.8% accuracy.


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