Volume 16, Issue 1

Vulnerability to extended power outages stemming from grid collapse triggered by terrorism, technological accident, cyber attack or geomagnetic storms is understood to mean the widest possible spectrum of immediate and downstream consequences for our nations critical infrastructure. Regrettably few realistic plans are in place for dealing with this risk especially as it pertains to three primary energy systems of strategic significance to the United States – nuclear power, chemical manufacturing and natural gas supplies. The author argues that greater sustained attention is needed to upgrade the resilience of these systems, foster greater sharing of remedies among them to offset the worst effects of grid collapse which exceeds 15 consecutive calendar days and build collective avenues of enhanced risk mitigation against such scenarios.

The domestic roles of Western armed forces are expanding. Although there is broad academic agreement that this trend is widespread, research on its implications has been relatively scarce. Here, I examine three debates that have emerged in the wake of expanding domestic military roles. They include: discussion on the origins of this trend between functionalists and politically-oriented scholars; its implications for civilian control and civil rights; and its effects on military-police convergence. This is followed by a call for more research on how the expanding domestic roles of Western armed forces relate to domestic civil-military collaboration, the management of military organizations, military visibility and reputation, perceptions of new tasks within the military, and the scale of this trend. A concluding section makes a case for drawing more academic attention to this phenomenon.

How risk is defined, the nature of methodologies used to assess risk, and the degree to which rare events should be included in a disaster risk analysis, are important considerations when developing policies, programs and priorities to manage risk. Each of these factors can significantly affect risk estimation. In Part 1 of this paper [Etkin, D. A., A. A. Mamuji, and L. Clarke. 2018. “Disaster Risk Analysis Part 1: The Importance of Including Rare Events.” Journal of Homeland Security and Emergency Management .] we concluded that excluding rare events has the potential to seriously underestimate the cumulative risk from all possible events, For example, of the 100 most expensive weather disasters in the US, the single most expensive event accounts for 16% of total economic impacts. Similarly, the worst explosion disaster accounts for 17% of the fatalities of the total 100 worst events. though including them can be very challenging both from a methodological and data availability perspective. Underestimating risk can result in flawed disaster risk reduction policies, resulting in insufficient attention being devoted to mitigation and/or prevention. In Part 2, we survey various governmental emergency management policies and methodologies in order to evaluate varying equations used to define risk, and to assess potential biases within disaster risk analyses that do comparative risk ranking. We find (1) that the equations used to define risk used by emergency management organizations are frequently less robust than they should or are able to be, and (2) that methodologies used to assess risk are often inadequate to properly account for the potential contribution of rare events. We conclude that there is a systemic bias within many emergency management organizations that results in underestimation of risk.

A successful Denial of Service attack on a CI can indirectly have devastating and irreversible effects to those that depend on its services. Furthermore, recent disruptions have raised concerns regarding the resiliency, security effectiveness and emergency preparedness of CIs and dependent resources. To address the persistent challenge of protecting CIs and maintaining the essential services they provide, this research offers emergency management personnel a conceptual framework to evaluate security effectiveness and estimate the cascading effects that may result from inadequate security measures. We combine the philosophy of multi-dimensional modeling, with the statistical engine of Bayesian Belief Networks to provide proactive, scenario-based interdependency analysis for CI protection and resiliency. The findings of this research resulted in a multi-dimensional approach that enables a heightened awareness of one’s risk-posture by highlighting the existence (strength) or absence (weakness) of relevant security factors. Through stakeholder risk-assessment, preemptive implementation of threat mitigation plans for dependent resources are permissible. Specifically, we provide this proof of concept, “what-if” analysis tool to assist in the reduction of vulnerabilities. To illustrate the conceptual framework, we provide a Healthcare and Public Health sector case study that evaluates the impact to a hospital patient given a successful DoS attack on a CI.