Analytical method to identify the number of containers to inspect at U.S. ports to deter terrorist attacks (CORE1204)

Summary: The requirement for 100% container scanning has been a burning topic, since U.S. Department of Homeland Security issued the initiative in order to prevent terrorists from smuggling weapons of mass destructions into the U.S. The paper explores how much it is reasonable to come down from the 100% inspection rate, if deterrence and cost of retaliation are considered in the model. Deterrence means the power to dissuade an attacker from attempting to smuggle weapons as opposite to use coerce or compel.  Retaliation cost describes the cost incurred by an attacker e.g. due to dismantling the attacker’s network. It is assumed the defender discloses in advance how many containers are inspected. The paper can be viewed here: https://www.researchgate.net.

[s2If is_user_logged_in()]

Full review: The study provides an economical model based on the game theory to estimate the optimal inspection rates in order to deter perpetrators from smuggling weapons into the U.S. The model assumes the customs or Border agency aims at minimizing the expected damages and cost of inspections while perpetrators are simultaneously trying to maximize their rewards. The used parameters are number of attackers, estimated damages, the cost of inspecting a container, the cost of a smuggling attempt, the cost of retaliation and the probability of detecting weapons. Retaliation cost describes the cost incurred e.g. due to dismantling the attacker’s network.  Cost of a smuggling attempt are the costs of acquiring, developing or manufacturing the weapons, and any logistical costs required to smuggle them into the U.S.  It is assumed the government agency announces publicly the inspection level and set of retaliation policies. Retaliation policy must pose a credible threat that means the governmental agency would retaliate even if that were not economically justified.

The study has four main limitations. First, the paper does not describe under what conditions the model works well or poorly. The quality of strategic and tactical intelligence, the efficiency of criminal investigation and prosecution processes, the extent of inter-agency cooperation and information sharing, the degree of private sector involvement and successfulness of awareness campaigns on retaliation policies are probably factors that influence on the model and its parameters. Second, the study does not provide numerical estimates to the parameters such as detection rates and cost of retaliation. Third, it is very unlikely that weapons of mass destructions are transported in containers into the U.S., what makes it difficult to assess the usefulness of the model in real life cases. Forth, costs of retaliation are not calculated and published by law enforcement agencies, thus criminals cannot make decision based on financial risks.

Despite of these limitations the CORE project can adapt the game theory and benefit from the paper. Traditionally law enforcement agencies highlight the number of seizures, arrests and successful prosecutions to measure operations and their impacts. The presented model brings two interesting components, a cost of crime attempt and a cost of retaliation. If criminal activities are financed and managed based on the same principles like legal ones, expected losses due to seizures of illicit goods or drugs are very likely calculated in the criminal business models. Consequently, making criminal business unprofitable is key to stop criminal activities. The approach enables to model the dynamic between costs and rewards from viewpoints of both law enforcement and criminal actors. In the other words, the model makes possible to study two dimensions in the Innovation Agenda, societal costs and friction costs caused by implemented security measures.

Reference: Bier, Vicki M. & Haphuriwat, N. (2011). Analytical method to identify the number of containers to inspect at U.S. ports to deter terrorist attacks. Annals of Operations Research, 187(1), 137–158.

CORE1204

[/s2If]