EMAIL SPAM DETECTION: A SYMBIOTIC FEATURE SELECTION APPROACH FOSTERED BY EVOLUTIONARY COMPUTATION

Pedro Sousa (), Paulo Cortez (), Rui Vaz (), Miguel Rocha () and Miguel Rio ()
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Pedro Sousa: Centro Algoritmi/Department of Informatics, Universidade do Minho, Braga, Portugal
Paulo Cortez: Centro Algoritmi/Department of Information Systems, Universidade do Minho, Guimarães, Portugal
Rui Vaz: Department of Information Systems, Universidade do Minho, Guimarães, Portugal
Miguel Rocha: CCTC/Department of Informatics, Universidade do Minho, Braga, Portugal
Miguel Rio: Department of Electric and Electronic Engineering, University College London, Torrington Place, London, U.K.

International Journal of Information Technology & Decision Making (IJITDM), 2013, vol. 12, issue 04, 863-884

Abstract: The electronic mail (email) is nowadays an essential communication service being widely used by most Internet users. One of the main problems affecting this service is the proliferation of unsolicited messages (usually denoted by spam) which, despite the efforts made by the research community, still remains as an inherent problem affecting this Internet service. In this perspective, this work proposes and explores the concept of a novel symbiotic feature selection approach allowing the exchange of relevant features among distinct collaborating users, in order to improve the behavior of anti-spam filters. For such purpose, several Evolutionary Algorithms (EA) are explored as optimization engines able to enhance feature selection strategies within the anti-spam area. The proposed mechanisms are tested using a realistic incremental retraining evaluation procedure and resorting to a novel corpus based on the well-known Enron datasets mixed with recent spam data. The obtained results show that the proposed symbiotic approach is competitive also having the advantage of preserving end-users privacy.

Keywords: Spam detection; content-based filtering; evolutionary algorithms; Naïve Bayes; feature selection (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1142/S0219622013500326

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