White Papers

Identifying Image Spam Based on Header and File Properties Using C4.5 Decision Trees and Support Vector Machine Learning

Category: Software and Web Development, Security

Overview Image spam poses a great threat to email communications due to high volumes, bigger bandwidth requirements, and higher processing requirements for filtering. This paper presents a feature extraction and classification framework that operates on features that can be extracted from image files in a very fast fashion. The features considered are thoroughly analyzed regarding their information gain. They present classification performance results for C4.5 decision tree and support vector machine classifiers. Lastly, they compare the performance that can be achieved using these fast features to a more complex image classifier operating on morphological features extracted from fully decoded images.

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Publisher: Institute of Electrical and Electronics Engineers
File Format: PDF
Date Published: Oct 14, 2008
Format: White Papers
Topics: Spam - E-mail Fraud - Phishing, Email

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