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Journal of Advances in Computer Networks
Article . 2014 . Peer-reviewed
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Image Content-Based “Email Spam Image” Filtering

Authors: Jianyi Wang; Kazuki Katagishi;

Image Content-Based “Email Spam Image” Filtering

Abstract

 Abstract—With the population of Internet around the world, email has become one of the main methods of communication among people. Due to the flood of online information, great amount of the spam emails brings troubles to people. The number of technical approaches of spam filtering are increasing which are mostly based on the text spam filtering technologies. But it is not very effective for test messages imbedded into images which are developing rapidly in recent years. In this paper, we propose an approach of spam image filtering. Our approach combines the characteristics of spam images with the corner point density to detect spam images. The effectiveness of the proposed approach is experimentally evaluated.

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    5
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Average
Average
gold
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