為了提高信息系統的安全性，本文將基于統計學習理論的支持向量機方法應用到入侵
檢測系統中，保證了在先驗知識不足的情況下,支持向量機分類器仍有較好的分類正確率，達到了能夠對系統異常情況準確預測的目的。該方法避免了基于傳統機器學習的局限性，保證了較強的推廣能力，從而使整個入侵檢測系統具有較好的檢測性能。
關鍵詞：入侵檢測；支持向量機；機器學習
Abstract: In order to improve the safety of information system, the method of SVM based on
statistics learning theory is used in the intrusion detection system, which ensures that SVM
classifier has the higher accuracy in the absence of transcendent knowledge, and achieve the aim that SVM can accurately predict the abnormal state of system. By the use of this method, the limitation of traditional machine learning method is avoided and ensure the stronger extension ability.,which make intrusion detection system to have the better detecting performance.
Key Word: intrusion detecting; support vector machine; machine learning