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Society For Risk Analysis Annual Meeting 2009

Risk Analysis: The Evolution of a Science

Session Schedule & Abstracts

* Disclaimer: All presentations represent the views of the authors, and not the organizations that support their research. Please apply the standard disclaimer that any opinions, findings, and conclusions or recommendations in abstracts, posters, and presentations at the meeting are those of the authors and do not necessarily reflect the views of any other organization or agency. Meeting attendees and authors should be aware that this disclaimer is intended to apply to all abstracts contained in this document. Authors who wish to emphasize this disclaimer should do so in their presentation or poster. In an effort to make the abstracts as concise as possible and easy for meeting participants to read, the abstracts have been formatted such that they exclude references to papers, affiliations, and/or funding sources. Authors who wish to provide attendees with this information should do so in their presentation or poster.

Common abbreviations

Probabilistic and Agent-Based Risk Analysis in DHS Sponsored by DARSG

Room: Baltimore B   1:30-3:00 PM

Chair(s): Steve Bennett

T3-B.1  13:30  RAPID: Supporting risk-informed strategic policy and resource allocation decisions at DHS. Cheesebrough T*, Stenzler J, Langbehn W, Hanson M; U.S. DHS Office of Risk Management and Analysis

Abstract: The U.S. Department of Homeland Security (DHS) was established in 2003 as the fusion of 22 existing Federal agencies and the creation of a number of new DHS offices and agencies. While the impetus for the Department’s formation was the terrorist attacks of September 11th, 2001, the Department’s mission also includes additional responsibilities in natural disaster preparedness, response, and recovery, as well as numerous border, maritime, and immigration activities. Securing the country from every conceivable threat is not feasible. In this complex and resource-constrained environment, the department is emphasizing the use of risk management, including quantitative and qualitative risk assessments, as the primary basis for policy and resource allocation decisions. This presentation will discuss lessons learned and current progress in the Risk Assessment Process for Informed Decision-making (RAPID), a risk assessment conducted within the DHS Office of Risk Management and Analysis that is intended to support strategic policy and budgetary decision-making across the Department. While a number of risk assessment activities are ongoing within DHS components, RAPID is the only assessment at the DHS headquarters level supporting decision-making across components. This assessment is intended to be used by DHS leadership for both strategic policy and budgetary planning and will support resource allocation decisions. A prototype for RAPID has recently been completed, and a more expansive second round is currently underway. While RAPID presents an important step toward using risk to inform policy and the allocation of resources, this assessment will continue to be refined and enhanced with each of the planned successive iterations. This presentation will give the audience a picture of some of the strategic risk analysis underway at the Department, as well as provide an opportunity for attendees to provide input and suggestions for improvement and enhancement.

T3-B.2  13:50  RMAP: Agent-based risk analysis for the aviation system. Cox A*, McKean M, Robinson R; Transportation Security Administration

Abstract: TSA will present RMAP---The Risk Management Analysis Process---as one of the analytic tools that TSA uses make risk-informed decisions and the TSA risk doctrine that governs how RMAP results are utilized in decision-making. RMAP includes the use of a set of simulation tools that utilizes agent-based modeling to provide risk insights on countermeasure effectiveness, adversary adaptation and threat-shifting, and economic consequences to the aviation system. TSA has been using RMAP since April of 2009. RMAP creates a simulation environment in which ‘red-agents’ seek out paths of least impedance in order to achieve an end-effect (e.g. destroying an airplane). Risk is measured as a function of attractiveness and consequence. Countermeasures are then placed in the environment to determine if the countermeasure achieves any risk reduction or if the adversary simply shifts to a new threat. TSA utilizes the model to inform technology investment decisions, risk mitigation strategies, and create requirements necessary for innovation initiatives. Because the salient feature of terrorism risk is deep uncertainty, TSA has developed a risk doctrine that emphasizes the dichotomy of unknown and known risks, avoidance of rigid prioritization, avoidance of false precision, and a bias towards risk mitigation measures which are robust across a portfolio of risk. TSA will discuss the interplay between deep uncertainty and risk simulation modeling to inform decisions as well as presenting lessons learned from the risk management process. Finally, TSA will also discuss the process of discovering and implementing risk mitigation strategies through the use of RMAP.

T3-B.3  14:10  Probabilistic risk analysis and bioterrorism risk. EZELL BE*, BENNETT SP, von Winterfeldt D, SOKOLOWSKI J, COLLINS AJ; OLD DOMINION UNIVERSITY

Abstract: There is only one logical and workable interpretation of probability and it is that of degrees of belief – G. Apostolakis (1990). Since the terrorist attacks of September 11th, 2001, and the subsequent establishment of the Department of Homeland Security (DHS), considerable effort has been applied to the challenge of risk analysis in the security domain. DHS, industry, and the academic risk analysis communities have all invested heavily in the development of tools and approaches that can assist decision makers in effectively allocating limited resources across the vast array of potential investments that could mitigate risks from terrorism and other threats to the homeland. While considerable progress has been made in approaches for terrorism risk analysis, there remain a number of challenges and limitations to each method currently in use. This presentation will explore a number of current and potential approaches for terrorism risk analysis, focusing particularly on recent discussions regarding the applicability of probabilistic, and decision analytic approaches in terrorism risk analysis. Some have argued that because of the adaptive nature of intentional adversaries, alternative tools to probabilistic risk analysis (PRA), like decision trees are superior for risk analysis of terrorist events. While we do not take issue here with the value of alternative approaches, this presentation aims to make a case 1) that PRA is an important and useful approach for quantifying terrorism risks and has value in guiding risk management decisions; 2) event trees can be used as part of a terrorism PRA to decompose the universe of terrorism scenarios; and 3) decision trees, like all approaches, have limitations. In the case of applications for terrorism risk analysis, decision tree limitations may be difficult to surmount in that the adversaries’ objective functions and level of ability to predict tree outcomes are unknown.

T3-B.4  14:30  A place for probability: Examining assumptions in optimizing methods for terrorism risk analysis. Bennett SP*, Ezell BC; U.S. DHS Office of Risk Management and Analysis

Abstract: The Department of Homeland Security (DHS) is responsible for managing a broad spectrum of the nationu2019s security, covering such diverse areas as counterterrorism and WMD defense, natural hazard preparedness and response, and border security. While DHS' role as a risk management organization is complicated by this diversity of mission areas, it is arguable that the security domain that presents some of the most significant technical challenges to the risk analysis community is that of terrorism. Illegal immigration frequencies and downstream consequences, while not uncontroversial, are nonetheless supported by statistical data. Similarly, while not trivial, estimation of natural disaster frequencies can nonetheless incorporate considerable historical information, as well as physical models built on well-understood phenomena. Risk analysis for terrorism is a different story. Unlike natural hazards or border crimes, many forms of terrorism in the U.S. (thankfully) have little supporting historical data to guide estimation of attack frequencies. Since senior DHS leadership requires an understanding of the risk of terrorism events, and further a mechanism to be able to place these risks alongside natural hazard and border risks for comparison and alternative tradeoff analyses, in the absence of historical or statistical data, how can terrorism frequencies or probabilities be estimated? Considerable debate is currently underway in the risk analysis community regarding methods for effectively representing the ?intelligent adversary," and recent discussions have focused on optimization methods based on decision analysis and game theory as potentially superior to probabilistic approaches for terrorism applications. In this presentation, we examine some foundational assumptions in a number of optimization approaches and advocate as a result of these assumptions that probabilistic approaches still retain value in providing risk-informed decision support to DHS leadership.

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