Dynamic recognition algorithm based on data field in immune intrusion detection

A construction method of detector and its relevant dynamic recognition algorithm were put forward by introducing the data field theory to computer immunology. Antibodies are brought up based on self set. By recognizing the unknown self set, the algorithm can decrease the rate of self-immunity, and also improve the antibody set dynamically and overcome the limitations of traditional IDs that have high requirement for self set, thus simplify the way to implement cloning, mutation and memory. The results of experiments show that the new dynamic recognition algorithm makes IDs possess a higher self adaptability and dynamic equilibrium capability.