项目名称: 面向网络安全态势感知的多尺度熵网络行为分析方法研究
项目编号: No.61300211
项目类型: 青年科学基金项目
立项/批准年度: 2014
项目学科: 自动化技术、计算机技术
项目作者: 周仁杰
作者单位: 杭州电子科技大学
项目金额: 23万元
中文摘要: 网络安全态势感知(NSSA)旨在对当前的网络安全状态进行实时监测和定量评估,并对未来一段时间内的网络安全趋势做出准确预测和预警。现有网络安全态势感知方法存在感知范围片面、网络安全态势衡量机制欠缺,无法对复杂网络行为进行有效建模等问题。针对上述问题,本项目提出面向网络安全态势感知的多尺度熵网络行为分析方法研究,从网络行为学角度研究建立网络安全态势感知数学模型,提高网络安全态势感知的准确性和全面性。首先,扩展多尺度熵理论并用于分析多时空尺度网络行为结构复杂度,揭示网络行为随时空尺度变化的特征;其次,利用洗牌原理分析各层面网络行为之间的关系,揭示正常状态下网络行为逐层演化的规律;最后,建立基于多尺度熵网络行为分析的网络安全态势感知数学模型,开辟将网络行为分析方法应用于网络安全态势感知中的新途径。本项目的顺利开展将为网络安全态势感知的研究提供新思路,为深化和完善态势感知提供重要的理论依据。
中文关键词: 网络安全态势感知;网络行为分析;多尺度熵;弹性多尺度熵;时空特性
英文摘要: Network Security Situation Awareness(NSSA) technologies are aimed to perform real-time monitoring and quantitative assessment of network security status and to make accurate forecast and early warning of the trends of network security. However, the NSSA technologies are characterized of weaknesses like incomplete perception,lower level of analytics, lack of mechanisms for measuring network security situation and ineffective modeling of complex network behavior. We, therefore, propose this piece of research on multi-scale entropy network behavior analysis aimming to build a mathematical model of network security situational awareness from the perspective of network behavior modeling. We firstly extend the multiscale entropy theory and then use it to analyze the structural complexity of the network behavior in multiple spatial and temporal scales for revealing the time- and space-scaling characteristics of network behavior; Secondly, the shuffling principle is leveraged to analyze the immpact between network behaviors in different network layers, for depicting the law of network behavior evolution. Finally,the network security situation awareness model based on multiscale entropy network behavior is built to find the way in which the analysis of multiscale entropy network behavior can be used in NSSA. The succe
英文关键词: network security situational awareness;network behavioral analysis;multiscale entropy;flexible multiscale entropy;spatiotemporal characteristics