Abstract: On the basis of author's previous research works, this paper integrates Immune Algorithm (IA) consisting of vaccine operator,mutation operator and other operators with Negative Selection Algorithm (NSA),called IA-NSA algorithm, to perform evolution of detector population, whose purposes are to quicken the process of affinity maturation and improve the efficiency of network intrusion detection. The algorithms of vaccine operator and adaptive extracting vaccines were given in detail. A novel network intrusion detection model and its algorithm based on IA-NSA were presented to establish anomaly detection. The network intrusion detection experiments based on IA-NSA algorithm and Clonal Selection Algorithm (CSA) were designed respectively, the experimental results show that the IA-NSA algorithm consisting of vaccine operator quickens the affinity maturation process of detector population and stably increases the detection rate along with increasing evolutionary generation. But in CSA-NSA algorithm,the affinity maturation process of detector population takes more time, the detection rate has a little degradation and maintains invariant for a long time.

Key words: hnmune algorithm, Vaccine operator, Clonal selection algorithm, Network intrusion detection