分析研究了人工免疫原理在網絡入侵檢測中應用的可行性，結合人工免疫模型和數據挖掘技術建立了一個網絡入侵檢測系統模型。對抗體生成過程中的關鍵算法進行了描述。為克服在抗體生成階段由于采用遺傳算子導致時空效率不佳的缺陷，將數據流分割成字符串集合，根據數理統計原理，討論了分割參數和檢測器數目的選定，使它在通用性、魯棒性上具有優勢。

The feasibility of applying artificial immune theory in intrusion detection system is Analyzed, establishes a model combining artificial immune theory and data mining technique is estoblished. Based on the statistical theory, the amount of information that is lost by splitting a data stream into unordered strings can be estimated, and this estimate can be used to guide the choice of string length. Based on information- theory, a lower bound on the size of the detector set is derived. Detector Generating algorithm is described. The performance of Artificial Immune Intrusion Detection System (AIIDS) is better than the normal intrusion detection system based on knowledge engineering.