Abstract: After analyzing the classification based on the represent points as the results of clustering algorithm with uniform granularity and distance function，the problem of this classification caused by that clustering result is inconsistent with a prior knowledge is pointed out.In order to solve this problem and improve the classification accuracy and the generalized ability，an immune clustering algorithm used different granularities is presented in this section.Experimental results show that the new method overcomes the problem to some extends，and this method has good results in intrusion detection compared with RBF-ANN and BP-ANN.