討論了將數據融合技術運用到入侵檢測系統中的方法，并提出了一個基于數據融合技術的入侵檢測機制－DFIDM。在該機制中，有多個檢測器搜集系統日志文件、網絡流量信息、網絡數據包等數據，這些數據在通過了本地決策、數據提取和對象提取階段等預處理過程之后，傳送到融合中心進行決策，重點研究了決策過程所涉及的多參數問題。為此，系統設計了檢測器可靠性、時間因素、空間因素等五個主要因素參與融合與決策。最后通過實驗證明，采用了該機制的入侵檢測系統具有更好的準確性。

This paper introduces a method of Intrude Detection Based on Data Fusion, and presents a new mechanism –DFIDM. In DFIDM, a few of sensors are configured to collect data, such as log file, information of Network Traffics and data package of network. After some pretreatments such as local decision-making, Data Refinement, Object Refinement, these data will be transferred to fusion center. In this paper, we mostly research the multiple parameters of final decision-making, such as reliability of sensors, the factor of time, the factor of space. As it showed by the research result this mechanism can improve the veracity of IDS.