A survey of image spamming and filtering techniques
A survey of image spamming and filtering techniques
Many techniques have been proposed to combat the upsurge in image-based spam. All the proposed techniques have the same target, trying to avoid the image spam entering our inboxes. Image spammers avoid the filter by different tricks and each of them needs to be analyzed to determine what facility the filters need to have for overcoming the tricks and not allowing spammers to full our inbox. Different tricks give rise to different techniques. This work surveys image spam phenomena from all sides, containing definitions, image spam tricks, anti image spam techniques, data set, etc. We describe each image spamming trick separately, and by perusing the methods used by researchers to combat them, a classification is drawn in three groups: header-based, content-based, and text-based. Finally, we discus the data sets which researchers use in experimental evaluation of their articles to show the accuracy of their ideas.
Image classification, Image spam, Spam filtering techniques
71-105
Attar, Abdolrahman
f5efd538-042a-4647-9d46-1370d3049b72
Rad, Reza Moradi
7cf68458-1991-4d35-96dc-b6433caeb6f9
Atani, Reza Ebrahimi
d0eabc08-4a74-4786-978c-62aa3b049fa1
June 2013
Attar, Abdolrahman
f5efd538-042a-4647-9d46-1370d3049b72
Rad, Reza Moradi
7cf68458-1991-4d35-96dc-b6433caeb6f9
Atani, Reza Ebrahimi
d0eabc08-4a74-4786-978c-62aa3b049fa1
Attar, Abdolrahman, Rad, Reza Moradi and Atani, Reza Ebrahimi
(2013)
A survey of image spamming and filtering techniques.
Artificial Intelligence Review, 40 (1), .
(doi:10.1007/s10462-011-9280-4).
Abstract
Many techniques have been proposed to combat the upsurge in image-based spam. All the proposed techniques have the same target, trying to avoid the image spam entering our inboxes. Image spammers avoid the filter by different tricks and each of them needs to be analyzed to determine what facility the filters need to have for overcoming the tricks and not allowing spammers to full our inbox. Different tricks give rise to different techniques. This work surveys image spam phenomena from all sides, containing definitions, image spam tricks, anti image spam techniques, data set, etc. We describe each image spamming trick separately, and by perusing the methods used by researchers to combat them, a classification is drawn in three groups: header-based, content-based, and text-based. Finally, we discus the data sets which researchers use in experimental evaluation of their articles to show the accuracy of their ideas.
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Published date: June 2013
Keywords:
Image classification, Image spam, Spam filtering techniques
Identifiers
Local EPrints ID: 480901
URI: http://eprints.soton.ac.uk/id/eprint/480901
ISSN: 0269-2821
PURE UUID: 8e89325b-4c5a-4e86-8f2b-e5f94527e237
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Date deposited: 10 Aug 2023 16:51
Last modified: 17 Mar 2024 01:12
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Contributors
Author:
Abdolrahman Attar
Author:
Reza Moradi Rad
Author:
Reza Ebrahimi Atani
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