Artificial immune system based methods for spam filtering

To solve the spam problem, many statistical learning methods and AIS methods have been proposed and applied. In essence, statistical learning methods and AIS methods have quite different origins, and they try to find the solutions from distinct aspects. In recent works, we proposed several hybrid methods, which combined immune theory with statistical methods in spam filtering. In this paper, we briefly review and analyze these works and possible extensions, and demonstrate the rationality of building hybrid immune models for spam filtering. In addition, a generic framework of an immune based model is presented, and online implementation strategies are given. It is well demonstrated that how to apply the immune based model to building an intelligent email server.