Identification of SPAM messages using an approach inspired on the immune system

T.S. Guzella, T.A. Mota-Santos, J.Q. Uchôa, W.M. Caminhas
2008 Biosystems (Amsterdam. Print)  
In this paper, an immune-inspired model, named innate and adaptive artificial immune system (IA-AIS) is proposed and applied to the problem of identification of unsolicited bulk e-mail messages (SPAM). It integrates entities analogous to macrophages, B and T lymphocytes, modeling both the innate and the adaptive immune systems. An implementation of the algorithm was capable of identifying more than 99% of legitimate or SPAM messages in particular parameter configurations. It was compared to an
more » ... ptimized version of the naïve Bayes classifier, which has been attained extremely high correct classification rates. It has been concluded that IA-AIS has a greater ability to identify SPAM messages, although the identification of legitimate messages is not as high as that of the implemented naïve Bayes classifier.
doi:10.1016/j.biosystems.2008.02.006 pmid:18395967 fatcat:nhqnwr65qnc2pcswlalkgkhd2u