Identifying Factors that Influence Terrorist Decisions and Target Selection

Currently, the U.S. Department of Homeland Security (DHS) elicits probabilistic judgements from the intelligence community on actions terrorists may take to attack the continental U.S. For example, how likely is the adversary to choose agent \u27x\u27 over \u27y\u27 or target \u27a\u27 over target \u27b\u27? Eliciting these types of judgements is difficult and time consuming. The National Academies and others have suggested that a better approach may be to elicit information on adversary\u27s preferences, perceptions, and capabilities and use this information to calculate probabilities of interest to DHS. Some terrorist groups are thinking about using weapons of mass destruction (WMD), each with its own values, perceptions of reality, and capabilities. This presentation details the findings on the factors & relationships among factors that lead to a terrorist decision to initiate an attack against the continental U.S. as well as target selection. To accomplish this, we assembled international experts in WMD, adversary modeling, political science, terrorism, psychiatry, social sciences as well as experts from national laboratories, the Commonwealth of Virginia State Fusion Center, and Hampton Roads Emergency Management. This paper provides a summary of the findings from an Adaptive Adversary Workshop. In this paper, we provide an overview of the motivation for and design of the workshop as well as 19 emerging themes. The purpose of the workshop was to illicit expert opinions on terrorist decision-making and target selections in an effort to improve our understanding of adversaries (individuals, local/regional groups, transnational groups, states) who may initiate a bioterrorism attack in the from of releasing biological agents upon U.S. interests. Furthermore, these expert opinions are intended to be used to inform Bayesian Belief Network (BBN) models of terrorist networks. These models must be informed or populated with substantive information about the intelligent and adaptive adversary who may initiate an attack. To this end, a conceptual framework, informed broadly by the social sciences community, is intended to capture the terrorists\u27 motivations, methods, and decision calculi

Integrating a Simple Traffic Incident Model for Rapid Evacuation Analysis

Road transportation networks are a segment of society\u27s critical infrastructure particularly susceptible to service disruptions. Traffic incidents disrupt road networks by producing blockages and increasing travel times, creating significant impacts during emergency events such as evacuations. For this reason, it is extremely important to incorporate traffic incidents in evacuation planning models. Emergency managers and decision makers need tools that enable rapid assessment of multiple, varied scenarios. Many evacuation simulations require high-fidelity data input making them impractical for rapid deployment by practitioners. Since there is such variation in evacuation types and the method of disruption, evacuation models do not require the high-fidelity data needed by other types of transportation models. This paper\u27s purpose is to show that decision makers can gain useful information from rapid evacuation modeling which includes a simple traffic incident model. To achieve this purpose, the research team integrated a generic incident model into the Real-time Evacuation Planning Model (RtePM), a tool commissioned by the U.S. Department of Homeland Security to help emergency planners determine regional evacuation clearance times in the United States. RtePM is a simple, web-based tool that enables emergency planners to consider multiple evacuation plans at no additional cost to the user. Using this tool, we analyzed a simple scenario of the United States\u27 National Capital Region (NCR) to determine the impact of traffic incidents when different destination routes are blocked. The results indicate significant variations in evacuation duration when blockages are considered

From Cyclones to Cybersecurity: A Call for Convergence in Risk and Crisis Communications Research

<p>Effective risk and crisis communication can improve health and safety and reduce harmful effects of hazards and disasters. A robust body of literature investigates mechanisms for improving risk and crisis communication. While effective risk and crisis communication strategies are equally desired across different hazard domains (e.g., natural hazards, cyber security), the extent to which risk and crisis communication experts utilize the "lessons learned" from scientific domains outside their own is suspect. Therefore, we hypothesized that risk and crisis communication research is siloed according to scientific disciplines at the detriment to the advancement of the field of risk communications research writ large. We tested this hypothesis by evaluating the disciplinarity of 5,264 published papers containing risk and crisis communication keywords using a combination of simple descriptive statistics, natural language processing, and hierarchical clustering. Finding that the risk communication research is siloed according to disciplinary lexicons, we present our findings as a call for convergence amongst our risk and crisis communication scholars to bridge across our silos. In so doing, we will increase our ability to affect transformative change in the efficacy of our risk and crises messages.</p&gt