Intrusion Detection Algorithm of Artificial Immune Based on Decision Tree and Genetic Algorithm

Aiming at solving the problem that there were large amounts of ineffective antibodies and the antibodies were lack of diversity in the traditional negative selection algorithm, this paper designed intrusion detection algorithm of artificial immune based on decision tree and genetic algorithm. The decision tree and the genetic algorithm were introduced into the traditional negative selection algorithm, the affinity between antibody and antigen was calculated using decision tree, the new formula of fitness was raised. The diversity of antibody set was measured by concentration of antibody, and the high concentration antibodies were replaced by the low concentration antibodies to achieve the diversity of the antibody set. When the quantity of the antibody set was kept at a constant, the nonself set space could be covered as large as possible so as to enhance the capability of the antibody set.