Skip to main content

Survey on Anti-spam Single and Multi-objective Optimization

  • Conference paper
ENTERprise Information Systems (CENTERIS 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 220))

Included in the following conference series:

Abstract

In this paper anti-spam filtering is presented as a cumbersome service, as opposing to a software product perspective. The human effort for setting up, adaptation, maintenance and tuning of filters for spam detection is stressed. Because choosing the proper scores (relevance) for the spam filters is essential to the accuracy of the anti-spam system and one of the biggest challenges for the Apache SpamAssassin project (the most widely adopted anti-spam open-source software), we present a survey on single and multi-objective optimization studies for this purpose. Our survey constitutes a contribution and a stimulus for further research on this open research topic, with particular emphasis on evolutionary multi-objective approaches.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. MessageLabs Ltd., MessageLabs Intelligence, http://www.messagelabs.co.uk/intelligence.aspx

  2. Schryen, G.: Anti-Measures: Analysis and Design. Springer, Heidelberg (2007)

    Google Scholar 

  3. Dnswl.org, http://www.dnswl.org/

  4. SpamHaus Project Organization, The SpamHaus Project, http://www.spamhaus.org/

  5. Geeknet Inc.: Pyzor, http://pyzor.sf.net/

  6. Prakash, V.V.: Vipul’s Razor, http://razor.sf.net/

  7. Sender Policy Framework (SPF) for Authorizing Use of Domains in E-Mail - version 1, http://www.ietf.org/rfc/rfc4408.txt

  8. DomainKeys Identified Mail (DKIM) Signatures, http://www.ietf.org/rfc/rfc4871.txt

  9. Duan, Z., Dong, Y., Gopalan, K.: DMTP: Controlling spam through message delivery differentiation. Computer Networks 51, 2616–2630 (2007)

    Article  Google Scholar 

  10. Apache SpamAssassin Project, http://spamassassin.apache.org/

  11. Grindstone for SPAM, http://sing.ei.uvigo.es/grindstone4spam

  12. LingSpam dataset, http://www.aueb.gr/users/ion/data/lingspam/public.tar.gz

  13. Spambase dataset, http://www.ics.uci.edu/~mlearn/MLRepository.html

  14. SpamAssasin dataset, http://spamassassin.apache.org/publiccorpus/

  15. PU1 dataset, http://www.iit.demokritos.gr/skel/i-config/downloads/pu1_encoded.tar.gz

  16. Androutsopoulos, I., Koutsias, J., Chandrinos, K., Spyropoulos, C.: An experimental comparison of naive Bayesian and keyword-based anti-spam filtering with personal e-mail messages. In: 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 160–167 (2000)

    Google Scholar 

  17. TREC 2005 Spam Track Public Corpus, plg.uwaterloo.ca/gvcormac/treccorpus (2005)

    Google Scholar 

  18. Findlay, D., Birk, S.: Logistic Regression and Spam Filtering. Master Thesis (2007)

    Google Scholar 

  19. Dudley, J., Barone, L., While, L.: Multi-objective spam filtering using an evolutionary algorithm Evolutionary Computation. In: IEEE World Congress on Computational Intelligence (CEC 2008), pp. 123 -130 (2008)

    Google Scholar 

  20. Deb, K., Pratap, A., Agrawal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation 6, 182–197 (2002)

    Article  Google Scholar 

  21. Fonseca, C., Fleming, P.: Genetic algorithms for multi-objective optimisation: formulation, discussion, and generalisation. In: Fifth International Conference on Genetic Algorithms, pp. 416–423 (1993)

    Google Scholar 

  22. Goldberg, D.: Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley Professional, Reading (1989)

    MATH  Google Scholar 

  23. López-Herrera, A., Herrera-Viedma, E., Herrera, F.: A Multiobjective Evolutionary Algorithm for Spam E-mail Filtering. In: 3rd International Conference on Intelligent System and Knowledge Engineering (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Yevseyeva, I., Basto-Fernandes, V., Méndez, J.R. (2011). Survey on Anti-spam Single and Multi-objective Optimization. In: Cruz-Cunha, M.M., Varajão, J., Powell, P., Martinho, R. (eds) ENTERprise Information Systems. CENTERIS 2011. Communications in Computer and Information Science, vol 220. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24355-4_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-24355-4_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24354-7

  • Online ISBN: 978-3-642-24355-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics