Target-oriented utility for interdiction of transportation networks

Optimal resource allocation in security has been a significant challenge for critical infrastructure protection. We study an optimal resource-allocation model for more cost-effective protection of critical targets on a transportation network. We apply target-oriented utility theory and use mixed-integer programming to determine the optimal level of investment needed to interdict an attacker on a transportation network. We assume that the attacker will choose one target among multiple targets to attack based on factors such as the attractiveness of targets to the attacker and the attack success probabilities, and will be deterred for sufficiently low attack success probabilities. Sensitivity analyses are conducted to illustrate how the optimal defensive strategy depends on parameters such as attacker success probabilities, attacker deterrence, target values, number of targets, and effectiveness of defensive investment.