任务关键系统生存性形式化建模与分析
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摘要
随着信息化时代的到来,各类任务关键系统得到了广泛的应用,这些系统提供的基本服务一旦中断将给国民经济和人民生活带来巨大的影响。传统安全措施虽然提高了系统的安全性,但各种入侵事件还是不断发生,为此必须考虑系统在入侵发生后仍能提供用户满意的服务,生存性是应对一切攻击、入侵和破坏的最佳途径。
生存性研究的焦点在于保证系统在遭受攻击、故障和意外事故后仍能及时完成其关键任务,研究涉及生存性设计和生存性分析两大领域。其中,生存性分析,特别是量化分析是一项重要的基础工作,着重研究如何评价系统的生存性。目标是提供一个标准的测评方案,对系统生存性的现状进行评估,对生存性的变化趋势进行预测,进而在理论上指导可生存系统的设计和实现。目前,生存性分析研究虽然取得了一些进展,但整体上还没有形成统一的分析规范,研究成果也较少考虑到在实际应用中的可行性。本文针对这种情况,以生存性分析问题为核心,对系统生存性建模及分析方法进行深入研究。
首先,研究基于复合属性的生存性指标体系模型。从指标内容、攻击阶段及测定标准三个不同侧面对生存性性能指标进行综合分析,提出一种系统反映生存性的指标体系,对其进行形式化描述并抽象出相应的数学模型。在此基础上,探讨指标体系在不同应用场景下的简化与扩展,结合实例说明指标体系在不确定型AHP－Fuzzy生存性评估方法中的具体使用,为系统生存性分析提供合理的依据。
其次,研究基于性能评估进程代数的系统生存性形式化建模方法。剖析影响生存性的本质特征,将服务请求与服务器、攻击者与服务器描述为不同的组件,从用户服务请求和攻击影响两个角度分别构建精确描述系统行为和性质的生存性模型,并比较两种建模角度的异同。对模型中参数的灵敏度进行分析,使构建的模型更加完善。性能分析结果表明,该模型能够正确地反映出系统生存性的关键属性,以此为基础实现具体的生存性分析。
再次,研究基于概率模型检测的系统生存性量化分析方法。将图理论分析与数值求解、统计、仿真等技术相结合,面向具有随机行为的连续时间马尔可夫链系统概率模型,针对不同程度的攻击故障及系统服务水平,使用连续随机逻辑建立生存性的形式化规约。借助概率模型检测工具PRISM对模型进行统计和分析,以图形化地形式表示出系统生存性自动分析结果。仿真试验结果验证了该方法在生存性量化分析中的合理性和有效性,可实现系统在不同环境下生存性的实时监控。
最后,研究基于序列蒙特卡罗的系统生存性预测方法。建立系统动态模型并获取系统在当前时刻生存性的先验PDF,然后在当前时刻观测值和观测似然模型的基础上,根据贝叶斯公式更新先验PDF。通过重采样,用加权样本组合逼近生存性的真实后验概率分布,实现对下一时刻系统生存性的预测。仿真试验结果表明SMC对于生存性具有较高的预测精度,从多个时间序列中展示出系统生存性的动态变化趋势,使面向生存性的管理从被动变为主动。
With the advent of information age, various mission-critical systems have been widely used, and once the basic services interrupt, an enormous impact will be imposed on the national economy and people' s living standards. Traditional security measures have improved system security, whereas kinds of invasions still occur. As a result, the ability of system to provide users with satisfied services after invasions must be taken into account. Survivability is the best way to deal with all attacks, incursions and destructions.
Research on survivability focuses on how to ensure that systems can complete their critical missions in time under attacks, accidents or failures. Two domains are involved in this research: design and analysis of survivability. Among them, survivability analysis, especially the quantitative analysis is an important and fundamental work, focusing on how to assess system survivability. The objective is to provide a normal evaluating scheme, which can assess the current status of system survivability, forecast survivability' s trend in various environments, and further direct the design and realization of survivable system basically. At present, researches on survivability have made some progress, but there is still no uniform analyzing criterion and the research achievements have not taken practical feasibility into account. Aiming at this, survivability analysis is taken as the core, and the modeling and analyzing methods for system survivability are studied deeply in this dissertation.
Firstly, index system model of survivability based on composite attribute is studied. Performance metrics of survivability are comprehensively summarized from the following three perspectives: index content, attack phases and evaluating standard. Then a framework for index system which can present survivability is proposed and formalized, furtherly the corresponding mathematical model are abstracted. On the basis, simplification and extension of the index system in various application backgrounds are discussed. Combined with an instance, index system is illuminated in uncertain AHP-Fuzzy survivability evaluation, which provides reasonable evidence for system survivability analysis.
Secondly, formal modeling method of system survivability based on performance evaluation process algebra is studied. By analyzing the essential characters affecting survivability, service request and server, intruder and server are described as different components. Namely survivability model which accurately depicts system behaviors and properties is constructed from perspectives of users' service requests and attack impact respectively, and then similarities and differences are compared. Sensitivity analysis for model parameters is performed to make the constructed model perfect. Performance analysis resuluts show that the model can reflect key attributes of system survivability exactly, on the basis of which to achieve specific survivability analysis.
Thirdly, quantitative analysis method of system survivability based on probabilistic model checking is studied. Graph theory analysis is combined with numerical solution, statistics and simulation technology. Oriented at the CTMC system probabilistic model with stochastic actions, then formal specification of survivability is identified by continuous stochastic logic according to different disasters degree and service levels. Ultimately, Prism, the probabilistic model checking tool, is used to do statistics and analysis, and automated analysis results are plotted as graphs. Simulation experiment results verify the reasonability and validity of this method in quantitative analysis for survivability, which helps to realize the real-time monitoring for system survivability under different environments.
Finally, forecasting method of system survivability based on Sequential Monte Carlo is studied. A dynamic model of system is founded and employed to acquire prior PDF of survivability at current time, and then Bayesian formula is used to update the prior PDF on the basis of observed data and measurement model. Samples with associated weights are used to approximate posterior probability density distribution of survivability in order to forecast survivability at the next moment. Simulation experiment results show that SMC has a higher forecasting precision, and exibit dynamic development trend of system survivability from several time sequences, which changes survivability management from passiveness to initiative.
生存性研究的焦点在于保证系统在遭受攻击、故障和意外事故后仍能及时完成其关键任务,研究涉及生存性设计和生存性分析两大领域。其中,生存性分析,特别是量化分析是一项重要的基础工作,着重研究如何评价系统的生存性。目标是提供一个标准的测评方案,对系统生存性的现状进行评估,对生存性的变化趋势进行预测,进而在理论上指导可生存系统的设计和实现。目前,生存性分析研究虽然取得了一些进展,但整体上还没有形成统一的分析规范,研究成果也较少考虑到在实际应用中的可行性。本文针对这种情况,以生存性分析问题为核心,对系统生存性建模及分析方法进行深入研究。
首先,研究基于复合属性的生存性指标体系模型。从指标内容、攻击阶段及测定标准三个不同侧面对生存性性能指标进行综合分析,提出一种系统反映生存性的指标体系,对其进行形式化描述并抽象出相应的数学模型。在此基础上,探讨指标体系在不同应用场景下的简化与扩展,结合实例说明指标体系在不确定型AHP－Fuzzy生存性评估方法中的具体使用,为系统生存性分析提供合理的依据。
其次,研究基于性能评估进程代数的系统生存性形式化建模方法。剖析影响生存性的本质特征,将服务请求与服务器、攻击者与服务器描述为不同的组件,从用户服务请求和攻击影响两个角度分别构建精确描述系统行为和性质的生存性模型,并比较两种建模角度的异同。对模型中参数的灵敏度进行分析,使构建的模型更加完善。性能分析结果表明,该模型能够正确地反映出系统生存性的关键属性,以此为基础实现具体的生存性分析。
再次,研究基于概率模型检测的系统生存性量化分析方法。将图理论分析与数值求解、统计、仿真等技术相结合,面向具有随机行为的连续时间马尔可夫链系统概率模型,针对不同程度的攻击故障及系统服务水平,使用连续随机逻辑建立生存性的形式化规约。借助概率模型检测工具PRISM对模型进行统计和分析,以图形化地形式表示出系统生存性自动分析结果。仿真试验结果验证了该方法在生存性量化分析中的合理性和有效性,可实现系统在不同环境下生存性的实时监控。
最后,研究基于序列蒙特卡罗的系统生存性预测方法。建立系统动态模型并获取系统在当前时刻生存性的先验PDF,然后在当前时刻观测值和观测似然模型的基础上,根据贝叶斯公式更新先验PDF。通过重采样,用加权样本组合逼近生存性的真实后验概率分布,实现对下一时刻系统生存性的预测。仿真试验结果表明SMC对于生存性具有较高的预测精度,从多个时间序列中展示出系统生存性的动态变化趋势,使面向生存性的管理从被动变为主动。
With the advent of information age, various mission-critical systems have been widely used, and once the basic services interrupt, an enormous impact will be imposed on the national economy and people' s living standards. Traditional security measures have improved system security, whereas kinds of invasions still occur. As a result, the ability of system to provide users with satisfied services after invasions must be taken into account. Survivability is the best way to deal with all attacks, incursions and destructions.
Research on survivability focuses on how to ensure that systems can complete their critical missions in time under attacks, accidents or failures. Two domains are involved in this research: design and analysis of survivability. Among them, survivability analysis, especially the quantitative analysis is an important and fundamental work, focusing on how to assess system survivability. The objective is to provide a normal evaluating scheme, which can assess the current status of system survivability, forecast survivability' s trend in various environments, and further direct the design and realization of survivable system basically. At present, researches on survivability have made some progress, but there is still no uniform analyzing criterion and the research achievements have not taken practical feasibility into account. Aiming at this, survivability analysis is taken as the core, and the modeling and analyzing methods for system survivability are studied deeply in this dissertation.
Firstly, index system model of survivability based on composite attribute is studied. Performance metrics of survivability are comprehensively summarized from the following three perspectives: index content, attack phases and evaluating standard. Then a framework for index system which can present survivability is proposed and formalized, furtherly the corresponding mathematical model are abstracted. On the basis, simplification and extension of the index system in various application backgrounds are discussed. Combined with an instance, index system is illuminated in uncertain AHP-Fuzzy survivability evaluation, which provides reasonable evidence for system survivability analysis.
Secondly, formal modeling method of system survivability based on performance evaluation process algebra is studied. By analyzing the essential characters affecting survivability, service request and server, intruder and server are described as different components. Namely survivability model which accurately depicts system behaviors and properties is constructed from perspectives of users' service requests and attack impact respectively, and then similarities and differences are compared. Sensitivity analysis for model parameters is performed to make the constructed model perfect. Performance analysis resuluts show that the model can reflect key attributes of system survivability exactly, on the basis of which to achieve specific survivability analysis.
Thirdly, quantitative analysis method of system survivability based on probabilistic model checking is studied. Graph theory analysis is combined with numerical solution, statistics and simulation technology. Oriented at the CTMC system probabilistic model with stochastic actions, then formal specification of survivability is identified by continuous stochastic logic according to different disasters degree and service levels. Ultimately, Prism, the probabilistic model checking tool, is used to do statistics and analysis, and automated analysis results are plotted as graphs. Simulation experiment results verify the reasonability and validity of this method in quantitative analysis for survivability, which helps to realize the real-time monitoring for system survivability under different environments.
Finally, forecasting method of system survivability based on Sequential Monte Carlo is studied. A dynamic model of system is founded and employed to acquire prior PDF of survivability at current time, and then Bayesian formula is used to update the prior PDF on the basis of observed data and measurement model. Samples with associated weights are used to approximate posterior probability density distribution of survivability in order to forecast survivability at the next moment. Simulation experiment results show that SMC has a higher forecasting precision, and exibit dynamic development trend of system survivability from several time sequences, which changes survivability management from passiveness to initiative.
引文
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