Abstract: The detector in the model of artificial immune system (ARTIS) has no ability of active learning．It is difficult to set detection radius and makes detection performance slow in specific applications．Inspired by the receptor editing and immune suppression in the theory of biological immune,a new model called REISAIS (Receptor Editing and Immune Suppression based Artificial Immune System) was proposed．The model gives the detector a certain degree of active learning ability through receptor editing in the tolerance and mature stages．Thereby,the detection rate of the model is improved．The introduction of the immunosuppressive mechanism makes the false alarm rate of the model to be effectivelly controlled．In this paper,the formal description of the detector and suppressor was presented and the performance of the model was analyzed．The effectiveness of receptor editing for improving the detection performance was also proved．Theoretical analysis and experimental results show that the REISAIS achieves better detection performance without setting detection radius compared with ARTIS model.

Key words: Artificial immune system,Receptor editing,Receptor revision,Immune suppression