Abstract: To improve the efficiency of the forensic analysis method on data mining, this paper proposes a new method for the forensic analysis of the behavior profiling on the longest frequent pattern which is constructed by immune clonal algorithm. Taking the behavior data and the candidate pattern of the frequent item sets as the antigen and the antibody respectively, the support of the antigen to the antibody as the function of affinity, the key attribute as the constraint condition, and the minimal support as the screening condition, the behavior profiling on the longest frequent pattern is built with the help of the immune clonal operation to antibody. The abnormal data are detected by the matching method that the audit data pass through the list items of the behavior profiling. The proposed method and the method on Apriori-CGA are applied in the same problem. The comparison results indicate that the setting up time of behavior profiling and the test time of abnormal data are dramaticly reduced. Therefore, the proposed method has a good ability in the efficiency of forensic analysis and electronic crime investigation.