In this paper, we propose an analogy based immune recognition method that focuses on the implement of the clone selection process and the negative selection process by means of analogy similarity. This method is applied in an IDS(Intrusion Detection System) following several steps. Firstly, the initial abnormal behaviours sample set is optimized through the combining of the AIS(Artificial Immune System) and the genetic algorithm. Then, the abnormity probability algorithm is raised considering the two sides of abnormality and normality. Finally, an intrusion detection system model is established based on the above algorithms and models.