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Published on: September 12, 2014
Estimating conditional probabilities of terrorist attacks: modeling adversaries with uncertain value tradeoffs
1Office of Risk Management and Analysis, National Protection and Programs Directorate, U.S. Department of Homeland Security, USA. evan.levine@dhs.gov
Summary
This study presents a novel method for estimating adversary attack probabilities by modeling their decision-making process through utility function uncertainty. This approach provides crucial data for security analyses and risk assessments.
Area of Science:
- Decision Science
- Security Analysis
- Risk Management
Background:
- Security decision-making relies on attack probability estimates.
- Estimating these probabilities is challenging due to limited adversary insight and utility function knowledge.
- Subject matter experts currently provide these estimates via direct elicitation.
Purpose of the Study:
- To develop a method for modeling adversary decision processes.
- To solve for conditional attack probabilities in closed form.
- To provide improved inputs for probabilistic risk assessments.
Main Methods:
- Utilizing uncertainty in utility function value tradeoffs.
- Extending value-focused thinking principles.
- Modeling the adversary's decision process.
Main Results:
- A closed-form solution for conditional attack probabilities.
- A method applicable to security and general business decision-making.
- Demonstration with illustrative examples.
Conclusions:
- The described method offers a robust way to estimate attack probabilities.
- This technique enhances the accuracy of security decision support.
- The approach is broadly applicable beyond security contexts.
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