International Journal of Science , Engineering and Management (IJSEM)

Monthly Journal for Science , Engineering and Management

Volume3,February 2018,

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

Authors:Dipalee Patil || S. R. Ghungrad

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..

Keywords: Spam, Ham, Artificial Neural Network, Image Spam, OCR

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DOI: 01.1617/vol5/iss2/pid41520


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Editor-in-Chief

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Dr.Muhammad Ishtiaq,
Mirpur University of
Science & Technology,
Mirpur, Azad Kasmir.

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IMPACT FACTOR: 2.7

ISSN(Online): 2456-1304

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Thomson Reuters ID : q-6288-2016.
ORCiD Research ID : 0000-0001-9540-6799

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ACCEPTANCE RATIO: 25%
ARTICLES PUBLISHED:00007
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Journal Code : IJSEM
Electronic ISSN : 2456-1304
Impact Factor : 2.7
Frequency : Monthly
Contact : editor@ijsem.org

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