Abstract
Spam (or junk email) has been a major problem on the Internet. A lot of solutions have been proposed to deal with it. However, with the evolvement of spammers’ techniques and the diversification of email content, the traditional anti-spam approaches alone are no longer efficient. In this paper, a new anti-spam Peer-to-Peer (P2P) model based on immunity was presented. Self, Nonself, Antibody, Antigen and immune cells in email system were defined. The model architecture, the process of Antigen presenting, clone selection and mutation, immune tolerance, immune response, life cycle of immune cells and some other immune principles were described respectively. The analyses of theory and experiment results demonstrate that this model enjoys better adaptability and provides a new attractive solution to cope with junk emails in P2P environment.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Carreras, X., Mrquez, L.: Boosting Trees for Anti-Spam Email Filtering. In: Proceedings of the 4th International Conference on Recent Advances in Natural Language Processing (RANLP 2001), Tzigov Chark, Bulgaria, September 2001, pp. 58–64 (2001)
Sahami, M., Dumais, S., Heckermany, D., Horvitz, E.: A Bayesian Approach to Filtering Junk E-mail. In: Proceedings of the AAAI Workshop on Learning for Text Categorization, Madison, Wisconsin, July 1998, pp. 55–62 (1998)
Androutsopoulos, I., Paliouras, G., Karkaletsis, V., Sakkis, G., Spyropoulos, C.D., Stamatopoulos, P.: Learning to Filter Spam E-mail: A Comparison of a Naive 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 (PKDD 2000), Lyon, France, September 2000, pp. 1–13 (2000)
Kolcz, A., Alspector, J.: SVM-based Filtering of E-mail Spam with Content-Specific Misclassification Costs. In: Proceedings of the TextDM 2001 Workshop on Text Mining, IEEE International Conference on Data Mining, San Jose, USA, November 2001, pp. 1048–1054 (2001)
Hall, R.J.: Channels: Avoiding Unwanted Electronic Mail. Communications of ACM, 85–102 (March 1998)
Zhang, H., Liu, Q.: Model of Chinese Words Rough Segmentation Based on NShortest- Paths Method. Journal of Chinese Information Processing 16, 1–7 (2002)
Zhou, F., Zhuang, L., Zhao, B.Y., Huang, L., Joseph, A.D., Kubiatowics, J.: Approximate Object Location and Spam Filtering on Peer-to-peer Systems. In: Proceeding of ACM/IFIP/USENIX International Middleware Conference, Rio De Janeiro, Brazil, June 2003, pp. 1–20 (2003)
Damiani, E., De Capitani di Vimercati, S., Paraboschi, S., Samarati, P.: P2P-Based Collaborative Spam Detection and Filtering. In: Proceedings of the Fourth International Conference on Peer-to-Peer Computing (P2P 2004), Zurich, Switzerland, August 2004, pp. 176–183 (2004)
Metzger, J., Schillo, M., Fischer, K.: A Multiagent-Based Peer-to-Peer Network in Java for Distributed Spam Filtering. In: Mařík, V., Müller, J.P., Pěchouček, M. (eds.) CEEMAS 2003. LNCS (LNAI), vol. 2691, pp. 616–625. Springer, Heidelberg (2003)
Tao, L.: Computer Immunology. Publishing House of Electronics Industry, Beijing (2004)
Jia-wei, H., Kamber, M.: Data Mining Concepts and Techniques. China Machine Press, Beijing (2002)
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 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Athens, Greece, July 2000, pp. 160–167 (2000)
Wu, C.-T., Cheng, K.-T., Zhu, Q., Wu, Y.-L.: Using Visual Features for Anti-Spam Filtering. In: Proceedings of the International Conference on Image Processing (ICIP 2005), Genoa, Italy, September 2005, pp. 509–512 (2005)
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
Wang, F., You, Z., Man, L. (2006). Immune-Based Peer-to-Peer Model for Anti-spam. In: Huang, DS., Li, K., Irwin, G.W. (eds) Computational Intelligence and Bioinformatics. ICIC 2006. Lecture Notes in Computer Science(), vol 4115. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11816102_70
Download citation
DOI: https://doi.org/10.1007/11816102_70
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37277-6
Online ISBN: 978-3-540-37282-0
eBook Packages: Computer ScienceComputer Science (R0)