Abstract
Spam messages are continually filling email boxes of practically every Web user. To deal with this growing problem, the development of high-performance filters to block those unsolicited messages is strongly required. An Antibody Network, more precisely SRABNET (Supervised Real-Valued Antibody Network), is proposed as an alternative filter to detect spam. The model of the antibody network is generated automatically from the training dataset and evaluated on unseen messages. We validate this approach using a public corpus, called PU1, which has a large collection of encrypted personal e-mail messages containing legitimate messages and spam. Finally, we compared the performance with the well known naïve Bayes filter using some performances indexes that will be presented.
Chapter PDF
References
O’Brien, C., Vogel, C.: Spam filters: Bayes vs. chi-squared; letters vs. words. In: ISICT 2003: Proceedings of the 1st international symposium on Information and communication technologies, Trinity College Dublin, pp. 291–296 (2003)
Tsymbal, A.: A case-based approach to spam filtering that can track concept drift. Technical Report TCD-CS-2004-15, Trinity College Dublin (2004)
Cunningham, P., Nowlan, N., Delany, S.J., Haah, M.: A case-based approach to spam filtering that can track concept drift. Technical Report TCD-CS-2003-16, Trinity College Dublin (2003)
Androutsopoulos, I., Koutsias, J., Chandrinos, K.V., Spyropoulos, C.D.: An experimental comparison of naïve Bayesian and keyword-based anti-spam filtering with personal e-mail messages. In: Proceedings of the 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 160–167 (2000)
Sahami, M., Dumais, S., Heckerman, D., Horvitz, E.: A Bayesian approach to filtering junk e-mail. In: AAAI 1998 Workshop on Learning for Text Categorization, pp. 55–62 (1998)
Graham, P.: A plan for spam (2003), Available at: http://paulgraham.com/spam.html
Drucker, H., Vapnik, V., Wu, D.: Support vector machines for spam categorization. IEEE Transactions on Neural Networks 10, 1048–1054 (1999)
Carreras, X., Màrquez, L.: Boosting trees for anti-spam email filtering. In: Proceedings of the 4th International Conference on Recent Advances in Natural Language Processing, Tzigov Chark, BG (2001)
Androutsopoulos, I., Paliouras, G., Karkaletsis, V., Sakkis, G., Spyropoulos, C.D., Stamatopoulos, P.: Learning to filter spam e-mail: A comparison of a naïve Bayesian and a memory-based approach. In: Proceedings of the Workshop on Machine Learning and Textual Information Access, 4th European Conference on Principles and Practice of Knowledge Discovery in Databases, pp. 1–13 (2000)
Oda, T., White, T.: Immunity from spam: An analysis of an artificial immune system for junk email detection. In: Proceedings of the 4th International Conference on Artificial Immune Systems (ICARIS), pp. 276–289 (2005)
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. 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 (CEC 2003), Canberra, Australia, pp. 390–396 (2003)
Secker, A., Freitas, A.A., Timmis, J.: AISEC: An artificial immune system for e-mail classification. In: Proceedings of the Congress on Evolutionary Computation, pp. 131–139 (2003)
Knidel, H., de Castro, L.N., Von Zuben, F.J.: A supervised constructive neuro-immune network for pattern classification. In: IJCNN 2006: Proceedings of the 2006 Conference on International Joint Conference on Neural Networks (2006)
de Castro, L.N., Von Zuben, F.J., de Deus Jr., G.A.: The construction of a Boolean competitive neural network using ideas from immunology. Neurocomputing 50, 51–85 (2003)
Knidel, H., de Castro, L.N., Von Zuben, F.J.: RABNET: a real-valued antibody network for data clustering. In: GECCO 2005: Proceedings of the 2005 conference on Genetic and evolutionary computation, pp. 371–372. ACM Press, New York (2005)
Segel, L.A., Perelson, A.S.: Computations in shape space: a new approach to immune network theory. In: Perelson, A. (ed.) Theoretical Immunology. SFI Series on Complexity, vol. 2, pp. 321–343. Addison-Wesley, Reading (1988)
Kohonen, T.: Self-organization and associative memory: 3rd edition. Springer, New York (1989)
Kohonen, T.: Self-organizing maps. Springer, Berlin (2000)
Zuchini, M.H.: Aplicações de mapas auto-organizáveis em mineração de dados e recuperação de informação. Master’s thesis, UNICAMP (2003)
Yang, Y., Pedersen, J.O.: A comparative study on feature selection in text categorization. In: Fisher, D.H. (ed.) Proceedings of ICML 1997, 14th International Conference on Machine Learning, Nashville, US, pp. 412–420. Morgan Kaufmann Publishers, San Francisco (1997)
Zhang, L., Zhu, J., Yao, T.: An evaluation of statistical spam filtering techniques. ACM Transactions on Asian Language Information Processing (TALIP) 3, 243–269 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bezerra, G.B., Barra, T.V., Ferreira, H.M., Knidel, H., de Castro, L.N., Von Zuben, F.J. (2006). An Immunological Filter for Spam. In: Bersini, H., Carneiro, J. (eds) Artificial Immune Systems. ICARIS 2006. Lecture Notes in Computer Science, vol 4163. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11823940_34
Download citation
DOI: https://doi.org/10.1007/11823940_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37749-8
Online ISBN: 978-3-540-37751-1
eBook Packages: Computer ScienceComputer Science (R0)