Modeling Interdependencies and Cascading Effects of Disasters on Critical Infrastructures

Modeling Interdependencies and Cascading Effects of Disasters on Critical Infrastructures

연구 분야: Infrastructure

학회: International Joint Conference on Knowledge Discovery, Knowledge Engineering, and Knowledge Management

Critical Infrastructure (CI) is vital for a modern economy, and ensuring its security is crucial. The potential incapacitation or destruction of CI could have severe consequences for national security, the economy, public health, and safety. This study specifically examines the primary effects of cyber/physical attacks on critical infrastructure, investigating hidden vulnerabilities, cyber-physical disruptions, and their cascading impacts. Our goal is to develop analytical methods that provide valuable insights for policymakers, aiding in informed decision-making. The analytical modeling-computational framework design includes (a) establishing a knowledge graph construct that offers an interoperable ontological framework to describe coordinated parts, cyber/physical objects with capabilities, interdependencies, and processes/activities. (b) developing interdependency standards and visualization tool to overlay multiple CIs and components; (c) introducing a weighted multi-layer influence network incorporating interdependencies across multiple CI sectors; (d) proving theoretical results about the monotonicity and submodularity of the influence function, with implications for computational complexity; and (e) developing a 2-stage scalable solution engine to solve and interpret the resulting instances. We demonstrate the usage of the system by (a) establishing the first influence system network model to reveal vulnerabilities with maximum cascading effects in communication sector, utilizing scalable computational advances to model the entire U.S. communication network; and (b) assessing air transportation security and biological intelligence of COVID 19 disease spread and its scope of impact to air transportation, economy, and population health. The analytic tools and computational framework enhance the capabilities of cybersecurity and infrastructure security leaders, providing improved assessment for decision-making. This contributes to better system analysis, content relevancy, and long-term objectives of assisting decision-makers in assessing disruptions, establishing policies, and designing effective mitigation strategies. Identifying critical nodes enhances both defense and offense strategies, optimizing resource allocation for maximum protection.