New data fusion model of intrusion detection——IDSFP

TIAN Jun-feng; ZHAO Wei-dong; DU Rui-zhong; CAI Hong-yun

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New data fusion model of intrusion detection——IDSFP

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- New data fusion model of intrusion detection——IDSFP
- Issue 6, Pages: 115-120(2006)
- 作者机构：
  
  1. 河北大学数学与计算机学院
  2. 河北大学数学与计算机学院,河北,保定,071002
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP393.08
- Published：2006
- 稿件说明：
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TIAN Jun-feng, ZHAO Wei-dong, DU Rui-zhong, et al. New data fusion model of intrusion detection——IDSFP[J]. 2006, (6): 115-120.
DOI：

TIAN Jun-feng, ZHAO Wei-dong, DU Rui-zhong, et al. New data fusion model of intrusion detection——IDSFP[J]. 2006, (6): 115-120. DOI：

摘要

以多传感器数据融合技术为基础

提出了新的入侵检测融合模型——IDSFP。其具有对多个IDS入侵检测系统的警报进行关联、聚合

产生对安全态势判断的度量

从而构成证据的特点。IDSFP应用D-S证据理论来形成对当前安全态势进行评估的信息

并动态地反馈、调整网络中各个IDS(intrusiondetectionsystem)

加强对与攻击意图有关的数据的检测

进而提高IDS检测效率

降低系统的误报率和漏报率。

Abstract

Based on multi-sensor data fusion technology

a new intrusion detection data fusion model-IDSFP was pre-sented.The model was characterized by correlating and merging alerts of different types of IDS

generating the measures of the security situation

thus constituting the evidence.Current security situation of network was evaluated by applying the D-S evidence theory

and various IDS of network were adjusted dynamically to strengthen the detection of the data which relates to the attack attempt.Consequently

the false positive rate and the false negative rate are effectively reduced

and the detection efficiency of IDS is accordingly improved.

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Related Institution

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