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Situational Awareness for Improving Network Resilience Management

机译：改善网络弹性管理的情境意识

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Computer networks, widely used by enterprises and individuals nowadays, are still vulnerable when facing traffic injection, human mistakes, malicious attacks and other failures though we spend much more time and cost on security, dependability, performability, survivability, and risk assessment to make the network provide resilient services. This is because these measures are commonly viewed as closely related but a practical means of linking them is often not achieved. Network resilience research brings together all the planning that the network can be managed at a holistic view of resilience management. This paper focuses on network resilience management from "reactive" paradigm to a "proactive" one through Situational Awareness (SA) of internal factors of network and external ones of complex, dynamic and heterogeneous network environment. After surveying the research of network resilience and resilience assessment in the network, we give a model to discuss how to construct awareness of resilience issues which includes four stages. The first step is to get the situational elements about what we are interested in. Second, to understand what happened and what is going on in the networks, pattern learning and pattern matching are exploited to identify challenge. Then, to make proactive resilience management, we need to predict challenges and look for potential ones at this stage. At the fourth stage, resilience management can help take actions of remediation and recovery according to the policy of defender and attacker. After that, the two players' behaviors of defender and attacker are modeled in the same model by using Extended Generalized Stochastic Game Nets (EGSGN) which combines Game theory into Stochastic Petri Nets. Finally, we give a case study to show how to use EGSGN to depict the network resilience situation in the same model.
机译：如今，企业和个人广泛使用的计算机网络在面对流量注入，人为错误，恶意攻击和其他故障时仍然很脆弱，尽管我们在安全性，可靠性，可执行性，可生存性和风险评估上花费了更多时间和成本，以使网络提供弹性服务。这是因为这些措施通常被认为是紧密相关的，但是往往无法实现将它们联系起来的实用方法。网络弹性研究汇总了可以在弹性管理的整体视图下管理网络的所有计划。本文通过网络内部因素和复杂，动态和异构网络环境外部因素的态势感知（SA），将网络弹性管理从“反应式”范式转变为“主动式”范式。在调查了网络弹性和弹性评估的研究之后，我们给出了一个模型来讨论如何构建对弹性问题的认识，该模型包括四个阶段。第一步是获取我们感兴趣的情境元素。其次，为了了解网络中发生的事情和正在发生的事情，利用模式学习和模式匹配来识别挑战。然后，要进行主动的弹性管理，我们需要在此阶段预测挑战并寻找潜在挑战。在第四阶段，弹性管理可以根据防御者和攻击者的策略帮助采取补救和恢复措施。之后，使用扩展的广义随机博弈网（EGSGN）将博弈论结合到随机Petri网中，从而在防御者和攻击者这两个玩家的行为中建立模型。最后，我们通过一个案例研究来说明如何使用EGSGN来描述同一模型中的网络弹性情况。

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