Document Type

Conference Proceeding

Publication Date

2018

Publication Title

Proceedings of the 15th International Joint Conference on e-Business and Telecommunications - Volume 1: BASS

Editor

Christian Callegari, Marten van Sinderen, Paulo Novais, Panagiotis Sarigiannidis, Sebastiano Battiato, Ángel Serrano Sánchez de León, Pascal Lorenz, and Mohammad S. Obaidat

Abstract

Email is one of the most common forms of digital communication. Spam is unsolicited bulk email, while image spam consists of spam text embedded inside an image. Image spam is used as a means to evade text-based spam filters, and hence image spam poses a threat to email-based communication. In this research, we analyze image spam detection using support vector machines (SVMs), which we train on a wide variety of image features. We use a linear SVM to quantify the relative importance of the features under consideration. We also develop and analyze a realistic “challenge” dataset that illustrates the limitations of current image spam detection techniques.

Comments

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Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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