A Simple Method for Filtering Image Spam

Image spam can easily circumvent widely text spam filters. It is a new trend of spam, and poses a great threat to email communications. In this paper, we give the definition of image spam firstly. Then we propose a simple method for filtering image spam, which utilizes file properties and histogram (gray histogram or color histogram). Finally, a preliminary experimental evaluation of our approach is reported on a personal dataset and Princeton benchmark dataset of spam images publicly available.

[1]  Tu Minh Phuong,et al.  An Efficient Method for Filtering Image-Based Spam E-mail , 2007, CAIP.

[2]  Fabio Roli,et al.  Image Spam Filtering Using Visual Information , 2007, 14th International Conference on Image Analysis and Processing (ICIAP 2007).

[3]  Mark Dredze,et al.  Learning Fast Classifiers for Image Spam , 2007, CEAS.

[4]  Tu Minh Phuong,et al.  An Efficient Method for Filtering Image-Based Spam , 2007, 2007 IEEE International Conference on Research, Innovation and Vision for the Future.

[5]  Kwang-Ting Cheng,et al.  Using visual features for anti-spam filtering , 2005, IEEE International Conference on Image Processing 2005.

[6]  Michael J. Swain,et al.  Color indexing , 1991, International Journal of Computer Vision.

[7]  James A. Herson,et al.  Image analysis for efficient categorization of image-based spam e-mail , 2005, Eighth International Conference on Document Analysis and Recognition (ICDAR'05).

[8]  Zhe Wang,et al.  Filtering Image Spam with Near-Duplicate Detection , 2007, CEAS.

[9]  Wanli Ma,et al.  Detecting Image Based Spam Email , 2006, ICHIT.

[10]  Yuchun Tang,et al.  Identifying Image Spam based on Header and File Properties using C4.5 Decision Trees and Support Vector Machine Learning , 2007, 2007 IEEE SMC Information Assurance and Security Workshop.

[11]  L. Shires.  Image , 2018, Victorian Literature and Culture.