View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Unitn-eprints Research A SURVEY OF LEARNING-BASED TECHNIQUES OF EMAIL SPAM FILTERING Enrico Blanzieri and Anton Bryl January 2008 (Updated version) Technical Report # DIT-06-056 A Survey of Learning-Based Techniques of Email Spam Filtering Enrico Blanzieri, University of Trento, Italy, and Anton Bryl University of Trento, Italy, Create-Net, Italy
[email protected] January 11, 2008 Abstract vertising pornography, pyramid schemes, etc. [68]. The total worldwide financial losses caused by spam Email spam is one of the major problems of the to- in 2005 were estimated by Ferris Research Analyzer day’s Internet, bringing financial damage to compa- Information Service at $50 billion [31]. nies and annoying individual users. Among the ap- Lately, Goodman et al. [39] presented an overview proaches developed to stop spam, filtering is an im- of the field of anti-spam protection, giving a brief portant and popular one. In this paper we give an history of spam and anti-spam and describing major overview of the state of the art of machine learn- directions of development. They are quite optimistic ing applications for spam filtering, and of the ways in their conclusions, indicating learning-based spam of evaluation and comparison of different filtering recognition, together with anti-spoofing technologies methods. We also provide a brief description of and economic approaches, as one of the measures other branches of anti-spam protection and discuss which together will probably lead to the final victory the use of various approaches in commercial and non- over email spammers in the near future.