Research on Decision-Making of IDS with Multiple Parameters

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, and object refinement, these data will be transferred to fusion center. In this paper, we mainly 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.