Abstract
Using electronic mail (e-mail) we can communicate freely and almost at no cost. It creates new possibilities for companies that can use e-mail to send advertisements to their clients (that is called direct-mailing). The term spam refers mostly to that kind of advertisements. Massively sent unsolicited e-mails attack many Internet users. Unfortunately, this kind of message can not be filtered out by simple rule-based filters. In this paper we will extend artificial immune system (AIS) proposed in [6] which is based on mammalian immune system and designed to protect users from spam. Generally AIS are also used to detect computer viruses or to detect anomalies in computer networks.
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References
1. S. Augustyniak, Spam costs, anti-spam pays (in Polish), 2004
2. L. N. de Castro, F. J. Von Zuben, Learning and Optimization Using the Clonal Selection Principle, IEEE Transactions on Evolutionary Computation, Special Issue on Artificial Immune Systems, 6 (3), pp. 239–251, 2002
3. D. Dasgupta, F. Gonzales, An Immunity-based Technique to Characterize Intrusions in Computer Networks, IEEE Trans. on Evolutionary Computation, vol. 6, N3, June 2002, pp. 281–291
4. P. K. Harmer, P. D. Wiliams, G. H. Gunsch, G. B. Lamont, An Artificial Immune System Architecture for Computer Security Applications, IEEE Trans. on Evolutionary Computations Computation, vol. 6, N3, June 2002, pp. 252– 279
5. S. A. Hofmeyr, S. Forrest, Architecture for an Artificial immune system, IEEE Trans. on Evolutionary Computation, vol. 8, N4, June 2000, pp. 443–473
6. T. Oda, T. White, Developing an Immunity to Spam, GECCO 2003, pp. 231– 242
7. F. Seredyński, P. Bouvry, D. R. Rutkowski, Anomaly Detection System for Network Security: Immunity-based Approach, IIPWM 2005, pp. 486–490
8. S. R. White, M. Swimmer, E. J. Pring, W. C. Arnold, D. M. Chess, J. F. Morar, Anatomy of a commercial-grade immune system. Technical report, IBM Thomas J. Watson Research Center, 2002
9. S. T. Wierzchoń, Artificial Immune Systems. Theory and Applications (in Polish), 2001
10. http://nospam-pl.net
11. http://spamassassin.apache.org/, spamassassin website
12. http://www.mail-abuse.com
13. http://www.nwlink.com/~jhanks/spam.html, spam addresses
14. http://www.sv-cs.com/spam.html, spam words
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Kawecki, K., Seredyński, F., Pilski, M. (2006). Controlling Spam: Immunity-based Approach. In: Kłopotek, M.A., Wierzchoń, S.T., Trojanowski, K. (eds) Intelligent Information Processing and Web Mining. Advances in Soft Computing, vol 35. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-33521-8_4
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DOI: https://doi.org/10.1007/3-540-33521-8_4
Publisher Name: Springer, Berlin, Heidelberg
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