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一个将网络安全指标与宏观经济相互依存关系建模相联系的框架。

A framework for linking cybersecurity metrics to the modeling of macroeconomic interdependencies.

作者信息

Santos Joost R, Haimes Yacov Y, Lian Chenyang

机构信息

Center for Risk Management of Engineering Systems, University of Virginia, Charlottesville, VA 22904, USA.

出版信息

Risk Anal. 2007 Oct;27(5):1283-97. doi: 10.1111/j.1539-6924.2007.00957.x.

Abstract

Hierarchical decision making is a multidimensional process involving management of multiple objectives (with associated metrics and tradeoffs in terms of costs, benefits, and risks), which span various levels of a large-scale system. The nation is a hierarchical system as it consists multiple classes of decisionmakers and stakeholders ranging from national policymakers to operators of specific critical infrastructure subsystems. Critical infrastructures (e.g., transportation, telecommunications, power, banking, etc.) are highly complex and interconnected. These interconnections take the form of flows of information, shared security, and physical flows of commodities, among others. In recent years, economic and infrastructure sectors have become increasingly dependent on networked information systems for efficient operations and timely delivery of products and services. In order to ensure the stability, sustainability, and operability of our critical economic and infrastructure sectors, it is imperative to understand their inherent physical and economic linkages, in addition to their cyber interdependencies. An interdependency model based on a transformation of the Leontief input-output (I-O) model can be used for modeling: (1) the steady-state economic effects triggered by a consumption shift in a given sector (or set of sectors); and (2) the resulting ripple effects to other sectors. The inoperability metric is calculated for each sector; this is achieved by converting the economic impact (typically in monetary units) into a percentage value relative to the size of the sector. Disruptive events such as terrorist attacks, natural disasters, and large-scale accidents have historically shown cascading effects on both consumption and production. Hence, a dynamic model extension is necessary to demonstrate the interplay between combined demand and supply effects. The result is a foundational framework for modeling cybersecurity scenarios for the oil and gas sector. A hypothetical case study examines a cyber attack that causes a 5-week shortfall in the crude oil supply in the Gulf Coast area.

摘要

分层决策是一个多维度过程,涉及多个目标的管理(包括相关指标以及成本、效益和风险方面的权衡),这些目标跨越大型系统的各个层次。国家是一个分层系统,因为它包含从国家政策制定者到特定关键基础设施子系统运营者等多类决策者和利益相关者。关键基础设施(如交通、电信、电力、银行等)高度复杂且相互关联。这些相互关联表现为信息流动、共享安全以及商品的物理流动等形式。近年来,经济和基础设施部门越来越依赖网络信息系统来实现高效运营以及产品和服务的及时交付。为确保我们关键经济和基础设施部门的稳定性、可持续性和可操作性,除了了解它们的网络相互依存关系外,还必须了解其固有的物理和经济联系。基于列昂惕夫投入产出(I - O)模型变换的相互依存模型可用于建模:(1)给定部门(或一组部门)消费转移引发的稳态经济影响;(2)对其他部门产生的连锁反应。为每个部门计算不可操作性指标;这是通过将经济影响(通常以货币单位表示)转换为相对于该部门规模的百分比值来实现的。历史上,诸如恐怖袭击、自然灾害和大规模事故等破坏性事件已显示出对消费和生产的级联效应。因此,需要动态模型扩展来展示需求和供应综合效应之间的相互作用。结果是为石油和天然气部门的网络安全情景建模建立了一个基础框架。一个假设的案例研究考察了一次导致墨西哥湾沿岸地区原油供应短缺5周的网络攻击。

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