网络态势评估的粗集分析模型  

A Rough Set Analysis Model of Network Situation Assessment

作　　者：卓莹[1] 何明[1] 龚正虎[1] 

机构地区：[1]国防科学技术大学计算机学院,湖南长沙410073

出　　处：《计算机工程与科学》2012年第3期1-5,共5页Computer Engineering & Science

基　　金：国家973基础研究发展规划资助项目(2009CB320503);国家863高技术研究发展计划资助项目(2008AA01A325)

摘　　要：互联网的飞速发展导致系统复杂性随之增加。传统网络管理无法满足需求,基于融合的网络态势感知成为未来发展的必然方向。作为网络态势感知的核心,态势评估能够集成单元网管,提供全面宏观的网络状态视图,为决策提供支持。本文从网络态势的特点和需求出发,引入粗集理论,借助其在机器学习、处理海量冗余信息、特征选择等方面的强大能力,提出了基于粗集分析的网络态势评估模型,给出形式化定义,并详细介绍了评估流程。评估流程包括建立决策表、数据预处理、态势因子选择、协调性判断、条件属性约简以及决策规则约简等步骤。实验验证了原型系统的效果和效率。The rapid development of the Internet leads to an increase in system complexity. Traditional network management can not meet the requirements, and it should evolve to fusion-based Cyberspace Situational Awareness （CSA）.As the core of CSA, Network Situation Assessment （NSA） can integrate unit network managements, give a comprehensive macroscopic view of network operation status, and provide decision support. This paper focuses on the characteristics and requirements of network situation and introduces a rough set theory which has the superiority in machine learning, dealing with massive redundancy information, feature selection, and so on. We propose a NSA model based on rough set analysis, gave a formal definition and discuss the assessment procedure in detail, which includes decision table establishment, data preprocessing, situation factor selection, consistency judgment, condition attribute reduction and decision rule reduction. The experiment results demonstrate the efficiency and effectiveness of the prototype system.

关 键 词：网络态势评估 数据融合 粗集分析 模型 

分 类 号：TP393.07[自动化与计算机技术—计算机应用技术]