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Detecting computer generated images for image spam filtering

Muataz Hazza, Zubaidah and Abdul Aziz, Normaziah (2012) Detecting computer generated images for image spam filtering. In: 2012 International Conference on Advanced Computer Science Applications and Technologies, 26-28 Nov. 2012, Kuala Lumpur.

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Image spam continues to be one of cyber security problem today. Spammers used image spam as a technique to by-pass conventional email filters. Anti-Spammers used image classification as a method to detect images spam by extracting different features of the image. One of the important features used is color features. Several works used different color analysis to differentiate image spam, most of these works used supervised methods trying to differentiate computer generated images which is mostly like to be a spam and natural images. Supervised methods have its weaknesses, such as high cost in computation, requires training data, and rapid changes in spammers behaviors. This paper develops an unsupervised method using HSL geometric model (Hue, Saturation, and Luminance) to distinguish computer generated (CG) and natural images. Rules and Heuristics are defined by using HSL variables. The proposed method mainly depends on Saturation and Lightness values and their histograms. Experiment results shows that the combination of these variables can give high classification accuracy results.

Item Type: Conference or Workshop Item (Full Paper)
Additional Information: 5505/38377
Uncontrolled Keywords: HSL; image spam; lightness; saturation; normalized histogram;
Subjects: T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Information and Communication Technology > Department of Computer Science
Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User: Ahmad Nazreen Mohd Shamsuri (PT)
Date Deposited: 23 Sep 2014 14:58
Last Modified: 23 Sep 2014 14:58
URI: http://irep.iium.edu.my/id/eprint/38377

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