Decision Analysis

CREATE’s decision analysis researchers use rigorous models to help make sound decisions in homeland security applications related to terrorism and other catastrophic risks. Topics include:

  • Representation of preferences and trade-offs using multiattribute value and utility models
  • Representation of risk attitudes
  • Modeling adversary beliefs and preferences
  • Representation of belief using joint probability distributions and Bayesian learning
  • Group decision making
  • Framing decision situations
  • Alternative generation
  • The identification (and minimization) of cognitive biases 
  • Implementing a decision culture within  enterprises

Game Theory is also applied to capture objectives and beliefs of adaptive adversaries threating critical infrastructure, including seaports, airports, wildlife/forests/fisheries, and high-crime urban areas. Limited resources must be allocated and scheduled efficiently, avoiding predictability while simultaneously accounting for adversaries’ responses to security coverage, adversary preferences, and uncertainty over such preferences and capabilities. Casting security allocation as a Stackelberg security game, our new algorithms have been used in multiple applications.


Detlof von Winterfeldt

University of Southern California 

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Richard John

University of Southern California

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Vicki Bier

University of Wisconsin-Madison

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Williams Burns

Decision Research

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Sam Chatterjee

 Pacific Northwest National Laboratory

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Robin Dillon-Merrill

Georgetown University 

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Gilberto Montibeller

Loughborough University

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Randolph Hall
University of Southern California
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Johannes Royset

University of Southern California

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Maged Dessouky

University of Southern California

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Jun Zhuang

University at Buffalo

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Bistra Dilkina

University of Southern California

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Sample Papers

  • Siebert, J. & von Winterfeldt, D. (2020). Comparative Analysis of Terrorists’ Objectives, Decision Analysis, February 2020,
  • von Winterfeldt, D., Farrow, S., John, R., Eyer, J., Rose, A., & Rosoff, H. (2020). Assessing the Benefits and Costs of Homeland Security Research: A Risk-Informed Methodology with Applications to the U.S. Coast Guard. Risk Analysis, 40(3), 450-475. doi: 10.1111/risa.13403 
  • Kusumastuti, S., Rosoff, H., & John, R. S. (2019). Characterizing conflicting user values for cyber authentication using a virtual public values forum. Decision Analysis, 16(3), 157-171. doi: 10.1287/deca.2018.
  • Cui,J., Nguyen, T., Pita, J., &  John, R. S. (2017). Methods for addressing the unpredictable real-world element in security. In A. Abbas, M. Tambe, & D. von Winterfeldt (Eds.), Improving homeland security decisions (pp. 574-603). Cambridge University Press.  
  • Rosoff, H. & John, R. S. (2017). Decision analysis by proxy for the adaptive adversary. In A. Abbas, M. Tambe, & D. von Winterfeldt (Eds.), Improving homeland security decisions (pp. 709-729). Cambridge University Press.
  • Cui, J., Rosoff, H., & John, R. S. (2017). Deterrence of cyber attackers in a three-player behavioral game. In S. Rass, B. An, C. Kiekintveld, F. Fang, & S. Schauer (Eds.), Decision and game theory for security: GameSec 2017 (pp. 718-736). New York: Springer.  
  • Nguyen, K., Rosoff, H., & John, R. S. (2017). Valuing equal protection in aviation security screening. Risk Analysis, 37(12), 2405-2419. doi: 10.1111/risa.12814
  • Garcia, R. & von Winterfeldt, D. (2016) Defender-attacker decision tree analysis to counter terrorism.  Risk Analysis, 36(8), 1-14.