基于人工免疫的新型入侵檢測(cè)系統(tǒng)研究

分析研究了人工免疫原理在網(wǎng)絡(luò)入侵檢測(cè)中應(yīng)用的可行性，結(jié)合人工免疫模型和數(shù)據(jù)挖掘技術(shù)建立了一個(gè)網(wǎng)絡(luò)入侵檢測(cè)系統(tǒng)模型。對(duì)抗體生成過(guò)程中的關(guān)鍵算法進(jìn)行了描述。為克服在抗體生成階段由于采用遺傳算子導(dǎo)致時(shí)空效率不佳的缺陷，將數(shù)據(jù)流分割成字符串集合，根據(jù)數(shù)理統(tǒng)計(jì)原理，討論了分割參數(shù)和檢測(cè)器數(shù)目的選定，使它在通用性、魯棒性上具有優(yōu)勢(shì)。

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.