Collaborative Research: CT-ER : MiMANSaS: Metrics, Models and Analysis of Network Security and Survivability

信息和通信技术（ICT）基础设施故障和网络攻击是可能产生灾难性社会影响的现实。信息保障（IA）可以定义为通过确保其可靠性和安全性来保护和维护ICT系统的操作。迫切需要有系统的信息保障方法，使信通技术系统能够适应和抵御任何类型的中断或攻击。IA技术发展的一个主要障碍是缺乏模型和指标，使人们能够确定IA机制的有效性。这个探索性的项目在不同机构的三个PI之间进行了合作：杜克大学、密苏里州堪萨斯市大学和匹兹堡大学，重点是开发指标和模型，使人们能够定量研究ICT基础设施网络组件的信息保证（IA）的技术方面。该方法的基础是统一的攻击树，攻击图，特权图和故障树到一个共同的可扩展的框架与一组定义良好的指标和应用场景。扩展的基本模型，包括状态信息，随机属性和回报，通过马尔可夫链和随机Petri网，使更广泛的各种攻击和故障的情况正在研究。 所开发的模型和指标的影响在于，它们提供了确定IA机制的有效性所必需的技术和工具，并允许人们检测瓶颈和评估信息保证、性能和成本水平之间的权衡。

Information and Communications Technology (ICT) infrastructure failures and cyber attacks are realities that can have catastrophic societal effects. Information Assurance (IA) can be defined as the operations undertaken to protect and defend ICT systems by ensuring their dependability and security. There is a critical need for systematic IA methods that enable ICT systems to adapt and survive any type of disruption or attack. A major hurdle in the development of IA techniques is the lack of models and metrics which enable one to determine the effectiveness of IA mechanisms. This exploratory project seeds a collaborative effort between three PIs at different institutions: Duke University, University of Missouri Kansas-City, and the University of Pittsburgh focused on the development of metrics and models that will allow one to quantitatively study the technical aspects of information assurance (IA) for the network component of the ICT infrastructure. The basis of the approach is to unify attack trees, attack graphs, privilege graphs and fault trees into a common scalable framework with a well defined set of metrics and application scenarios. Extensions of the basic model that include state information, stochastic properties and rewards via Markov chains and stochastic Petri nets, enabling a wider variety of attack and fault scenarios are being studied. The impact of the models and metrics developed is that they provide the techniques and tools necessary to determine the effectiveness of IA mechanisms and allow one to detect bottlenecks and to evaluate the tradeoffs between levels of information assurance, performance and cost.