Modeling Adversaries in Counterterrorism Decisions Using Prospect Theory.

Area of Science:

• Decision Analysis
• Game Theory
• Behavioral Economics

Background:

• Counterterrorism decision-making models traditionally assume rational utility maximization by attackers.
• Empirical research indicates human decision-making deviates from expected utility, exhibiting loss aversion and likelihood insensitivity.
• Existing models lack descriptive accuracy regarding attacker psychology.

Purpose of the Study:

• To modify existing counterterrorism decision models by integrating prospect theory for attacker behavior.
• To descriptively model attacker loss aversion and likelihood insensitivity.
• To analyze the impact of these psychological factors on defender strategies in critical security scenarios.

Main Methods:

• Utilized a hybrid approach combining decision analysis and game theory.
• Employed expected utility theory for the defender's rational decision-making paradigm.
• Applied prospect theory to model the attacker's decision-making process, incorporating loss aversion and likelihood insensitivity.
• Examined the specific case of screening containers for radioactive materials entering the United States.

Main Results:

• The defender's optimal strategy is significantly influenced by the attacker's degree of loss aversion.
• Attacker likelihood insensitivity also impacts the effectiveness of defender decisions.
• Ignoring these behavioral aspects can lead to suboptimal security outcomes.

Conclusions:

• Integrating prospect theory provides a more descriptively accurate model of attacker behavior in counterterrorism.
• Defender strategies must adapt to account for psychological biases like loss aversion and likelihood insensitivity.
• Understanding these behavioral nuances is crucial for optimizing national security decisions, such as container screening.