International Journal of Engineering Research in Electronics and Communication Engineering

Comparative Study of Efficient Neural Network Methodology for Text & Image Based Spam Email Filteration

Author : Dipalee Patil ¹ S. R. Ghungrad ²

Date of Publication :7th February 2018

Abstract: Internet users frequently use e-mail for fast data communication of audio, video and textual data but at the same time, they are facing problem due to unwanted e-m3ail known as spam e-mail. In order to filter this unwanted e-mail, a classifier must be placed in the network or in the computer. Spam e-mail with advertisement text embedded in images presents a great challenge to anti-spam filters. In this paper, we present a fast method to detect image-based spam e-mail. To achieve the objective, Artificial Neural Network is applied for the classification of spam and ham emails. OCR-based modules can be used against image spam, to tolerate the analysis of the semantic content embedded into images

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