Quantifying Adversary Capabilities to Inform Defensive Resource Allocation.
We propose a Bayesian Stackelberg game capable of analyzing the joint effects of both attacker intent and capabilities on optimal defensive strategies. The novel feature of our model is the use of contest success functions from economics to capture the extent to which the success of an attack is attributable to the adversary's capability (as well as the level of defensive investment), rather than pure luck. Results of a two-target example suggest that precise assessment of attacker intent may not be necessary if we have poor estimates of attacker capability.
Department of Industrial Engineering, Tsinghua University, Beijing 100084, China.
Chen
C
Wang
Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI, USA.
Vicki M
VM
Bier
Adversary capability; Stackelberg game; homeland security; uncertainty