Abstract
Despite attempts to legislate them out of existence, spam messages (junk email) continue to fill electronic mailboxes around the world. With spam senders adapting to each technical solution put on the market, adaptive solutions are being incorporated into new products. This paper undertakes an extended examination of the spam-detecting artificial immune system proposed in [1,2], focusing on comparison of scoring schemes, the effect of population size, and the libraries used to create the detectors.
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Oda, T., White, T.: Developing an immunity to spam. In: Cantú-Paz, E., Foster, J.A., Deb, K., Davis, L., Roy, R., O’Reilly, U.-M., Beyer, H.-G., Kendall, G., Wilson, S.W., Harman, M., Wegener, J., Dasgupta, D., Potter, M.A., Schultz, A., Dowsland, K.A., Jonoska, N., Miller, J., Standish, R.K. (eds.) GECCO 2003, Part I. LNCS, vol. 2723, pp. 231–242. Springer, Heidelberg (2003)
Oda, T., White, T.: Increasing the accuracy of a spam-detecting artificial immune system. In: Proceedings of the Congress on Evolutionary Computation, Canberra, Australia, December 2003, vol. 1, pp. 390–396 (2003)
Templeton, B.: Reflections on the 25th anniversary of spam (2003)
Postini Inc.: Postini - email stats (2005) (accessed April 2005)
MessageLabs Ltd.: Monthly report: February 2005. Intelligence Newsletter (2005)
Controlling the assault of non-solicited pornography and marketing (CAN-SPAM) act of 2003 (2003) S. 877 as it was passed by the US Senate
Asaravala, A.: With this law, you can spam. Wired News (2004)
Secker, A., Freitas, A., Timmis, J.: AISEC: An Artificial Immune System for E-mail Classification. In: Proceedings of the Congress on Evolutionary Computation, Canberra. Australia, December 2003, pp. 131–139. IEEE, Los Alamitos (2003)
Sullivan, T.: The myth of spam volatility. QAQD.com White Paper (2004); Presented at the 2004 MIT Spam Conference (2004)
Apache Software Foundation: Spamassassin (2005), http://spamassassin.org
Pantel, P., Lin, D.: Spamcop: A spam classification & organization program. In: Learning for Text Categorization: Papers from the 1998 Workshop, Madison, Wisconsin, AAAI Technical Report WS-98-05 (1998)
Sahami, M., Dumais, S., Heckerman, D., Horvitz, E.: A bayesian approach to filtering junk E-mail. In: Learning for Text Categorization: Papers from the 1998 Workshop, Madison, Wisconsin, AAAI Technical Report WS-98-05 (1998)
Graham, P.: A plan for spam. Hackers & Painters (2002)
SpamBayes: Bayesian anti-spam classifier written in python (2004), http://spambayes.sourceforge.net/ (accessed October 13, 2004)
Graham, P.: Better bayesian filtering. In: 2003 Spam Conference (2003)
SpamAssassin public corpus (2003), http://spamassassin.org/publiccorpus/
Anderson, R.: Filters take a bite out of spam. Network Computing (2004)
Metz, C.: Spam blockers. PC Magazine (2004)
Free Software Foundation: Mailman (2005), http://www.list.org
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Oda, T., White, T. (2005). Immunity from Spam: An Analysis of an Artificial Immune System for Junk Email Detection. In: Jacob, C., Pilat, M.L., Bentley, P.J., Timmis, J.I. (eds) Artificial Immune Systems. ICARIS 2005. Lecture Notes in Computer Science, vol 3627. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11536444_21
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DOI: https://doi.org/10.1007/11536444_21
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