In the recent years spam became as a big problem of Internet and electronic communication. There developed a lot of techniques to fight them. In this paper the overview of existing e-mail spam filtering methods is given. The classification, evaluation, and comparison of traditional and learning-based methods are provided. Some personal anti-spam products are tested and compared. The statement for new approach in spam filtering technique is considered.
E. Gabber, M. Jakobsson, Y. Matias and A.J. Mayer, “Curbing Junk E-Mail via Secure Classification,” Proceedings of the Second International Conference on Financial Cryptography, Springer-Verlag London, 23-25 March 1998, pp. 198-213.
P. Boldi, M. Santini and S. Vigna, “PageRank as a Function of the Damping Factor,” Proceedings of the 14th International Conference on World Wide Web, ACM New York, 10-14 May 2005. doi:10.1145/1060745.1060827
L. M. Spracklin and L. V. Saxton, “Filtering Spam Using Kolmogorov Complexity Estimates,” in Russian, 21st International Conference on Advanced Information Networking and Applications Workshops (Ainaw’07), Niagara Falls, 21-23 May 2007, pp. 321-328.
S. V. Korelov, A. K. Kryukov and L. U. Rotkov, “Text Messages’ Digital Analysis on Spam Identification,” in Russian, Proceedings of Scientific Conference on Radiophysics, Nizhni Novgorod State University, Nizhny Novgorod Oblast, 2006.
S. M. Lee, D. S. Kim and J. S. Park, “Spam Detection Using Feature Selection and Parameters Optimization,” IEEE International Conference on Intelligent and Software Intensive Systems, Krakow, 15-18 February 2010, pp. 883-888. doi:10.1109/CISIS.2010.116
M. F. Saeddian and H. Beigy, “Spam Detection Using Dynamic Weighted Voting Based on Clustering,” Proceedings of the 2008 Second International Symposium on Intelligent Information Technology Application, Vol. 2, pp. 122-126. doi:10.1109/IITA.2008.140
M. Sasaki and H. Shinnou, “Spam Detection Using Text Clustering,” IEEE Proceedings of the 2005 International Conference on Cyberwords, Singapore, 23-25 November 2005, pp. 316-319. doi:10.1109/CW.2005.83
P. Cortez, C. Lopes, P. Sousa, M. Rocha and M. Rio, “Symbiotic Data Mining for Personalized Spam Filtering,” IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, Milan, 15-18 September 2009, pp. 149-156.
K. S. Xu, M. Kliger, Y. Chen, P. J. Woolf and A. O. Hero, “Revealing Social Networks of Spammers through Spectral Clustering,” IEEE International Conference on Communications, Dresden, 14-18 June 2009, pp. 1-6.
R. Segal, J. Crawford, J. Kephart and B. Leib, “SpamGuru: An Enterprise Anti-Spam Filtering System,” IBM Thomas J. Watson Research Center.
T.-J. Liu, W.-L. Tsao and C.-L. Lee, “A High Performance Image-Spam Filtering System,” Ninth International Symposium on Distributed Computing and Applications to Business, Engineering and Science, 10-12 August 2010, Hong Kong, pp. 445-449. doi:10.1109/DCABES.2010.97
M. Soranamageswari and C. Meena, “Statistical Feature Extraction for Classification of Image Spam Using Artificial Neural Networks,” Second International Conference on Machine Learning and Computing, Bangalore, 9-11 February, 2010, pp. 101-105.
F. Weidong and D. Shoubin, “Addressing Interest Diversity in P2P Based Collaborative Spam Filtering,” Fifth International Conference on Grid and Cooperative Computing Workshops, Hunan, October 2006, pp. 163-169.
P. A. Chirita, J. Diederich and W. Nejdl, “MailRank: Using Ranking for Spam Detection,” Proceedings of the 14th ACM International Conference on Information and Knowledge Management, Bremen, 31 October-5 November 2005.
R. Bhuleskar, A. Sherlekar and A. Pandit, “Hybrid Spam E-Mail Filtering,” 2009 First International Conference on Computational Intelligence, Communication Systems and Networks, Indore, 23-25 July 2009, pp. 302-307.