The dissertation mainly aims at applying several active machine learning strategies to intrusion detection and systematically studies signal analysis techniques of intrusion detection based on statistical learning theory ( slt ), symbol inductive learning theory and genetic learning method . meanwhile, performance comparison and evaluation among intrusion detection techniques based on different machine learning strategies are presented according to computational learning theory and statistical hypothesis test methodology . intrusion detection is regarded as a pattern recognition problem in term of statistical learning theory; i 本文的主要工作是將目前幾種有生命力的機器學習策略應用于入侵檢測技術中,論文從入侵檢測的不同視角出發,系統深入地研究了統計學習理論、基于符號的歸納學習理論和遺傳學習方法在入侵檢測信號分析中的應用技術,并在可能近似正確(pac)學習框架下,利用計算學習理論和統計假設檢驗方法對基于不同機器學習策略的入侵檢測方法進行了性能比較和評估。