Identifying Extreme Risks in Critical Infrastructure Interdependencies

Abstract

Critical infrastructures like our power generation facilities and water supply form highly interconnected networks that are mutually dependent and any failure can cascade through the network, resulting in devastating impact on health, safety and the economy. These catastrophic events/disruptions can be triggered by environmental accidents, geological/weather phenomena, disease pandemics, etc. The disruptions can be caused/exacerbated by their being unexpected, but they may actually be expected if relevant data have been accounted for. To help account for and thereby anticipate such disruptions, one way is to identify potential unforeseen interdependencies among infrastructure components that can lead to extreme disruptions upon some failure in the network. This paper shows how a simulation model for cascading failures and a risk analysis/optimization approach can be applied to search for unforeseen interdependencies and failure points that give rise to the highest risk in a network.

Vulnerability and risk assessment for operating system (OS) with framework STRIDE: comparison between VulnOS and Vulnix

“…Considering that the complexity and heterogeneity of networks built in a company's specific environment have simultaneously reduced the efficiency of network administrators [39], vulnerabilities assessment and analysis regularly can support the employees in giving the confidence in order to prepare themselves through training and understanding for proper control and handling 1651 activity. It is doubtful that some modeling and analysis could accurately and clearly predict how such an attack would occur on the network infrastructure, resulting in a shutdown or disruption, followed by a collision as the consequences [40], [41]. But at the very least, it can presents a depiction and alternative solution for prediction and preparation for the organization.…”

Modelling of critical infrastructure interdependencies for vulnerability analysis

“…Since critical infrastructure can be described through its network and the linkage between infrastructures can be used to describe the inter-relations among them, the network approach becomes a natural candidate for interdependency studies. The performance of an infrastructure can be analysed by modelling the component failure from the hazard at a component level, and then simulating the cascading failure within the modelled network at a system level (Tai et al, 2013). Lam et al (2013) demonstrated that by modelling the relationships and observing how disruption cascades within a complex infrastructure system, vulnerabilities can be identified, enabling planning for recovery and response.…”

“…Understanding the large-scale critical infrastructure network and its interdependencies can help us identify the interdependent links and their corresponding strengths (Santos et al, 2007;Wang et al, 2013;Tai et al, 2013;Kizhakkedath et al, 2013), and enables the development of a model to evaluate and predict the impact of a disruption, including the cascading and overall impact to economic sectors that are linked by these interdependencies. This can aid stakeholders in analysing worst case scenarios (Lam et al, 2013;Lin et al, 2016a;Lin et al, 2016b) These advantages may be helpful in the current research as critical infrastructure network analysis requires a model that is able to link infrastructure together, according to physical and logical interdependencies (Rinaldi et al, 2001).…”

“…The failure scenarios within the physical infrastructure network, comprising of one-node failures, two-node failures and three-node failures, are simulated by assuming different combinations of failed nodes and computing the resulting impact on all critical infrastructure sectors interconnected in the I/O model (Kizhakkedath et al, 2013;Lam et al, 2013;Tai et al,2013). 5.2 through Equation (3.9) to find the total impact to all sectors (∆X), which will evaluates the overall losses across all critical infrastructures due to the initial losses calculated through the network performance losses as described in Figure 5-4.…”