Security at major locations of economic or political importance is a
key concern around the world, particularly given the threat of
terrorism. Limited security resources prevent full security coverage at
all times, which allows adversaries to observe and exploit
patterns in selective patrolling or monitoring, e.g. they can plan an
attack avoiding existing patrols. Hence, randomized patrolling or monitoring is important, but randomization must provide distinct weights to different actions based on their complex costs and benefits, as well as adversary reactions.
Game theory provides us a framework to take all the costs and benefits into consideration, including adversary reactions, and provide a randomized schedule. While our ARMOR program, based on game theoretic foundations has been deployed at LAX international airport since August 2007, IRIS provides randomized schedules for the Federal Air Marshals and is undergoing evaluation for deployment. Other randomization programs are currently being developed.
The ARMOR software casts the above patrolling/monitoring problem as a Bayesian Stackelberg game, allowing the agent to appropriately weigh the different actions in randomization, as well as uncertainty over adversary types. ARMOR combines three key features:
It uses the fastest known solver for Bayesian Stackelberg games called DOBSS (Decomposed Optimal Bayesian Stackelberg Solver,
where the dominant mixed strategies enable randomization
Its mixed-initiative based interface allows users to occasionally adjust or override the automated schedule based on their
local constraints
It alerts users if mixed-initiative overrides appear to degrade the overall desired randomization
ARMOR has been sucessfully deployed since August 2007 at the Los Angeles International Airport (LAX) to randomize checkpoints on the
roadways entering the airport and canine patrol routes within the airport terminals.
With approximately 29,000 commercial flights per day in United States airspace, the Federal Air Marshal Service (FAMS) prioritizes allocation of resources based on risk. The current process follows the FAMS Concept of Operations and the DHS risk methodology by assigning FAM deployments based on consequence, vulnerability and threat. FAMS continually looks for process improvements to most efficiently mitigate the risks from the highest risk flights. One process improvement FAMS is currently examining is the ARMOR application. This application could aid FAMS in applying randomness in selection of a set of high risk flights to increase terrorist uncertainty of FAMS deployments.
ARMOR has been currently in evaluation by the Federal Air Marshal Service.
The Transportation Security Administration (TSA) is currently evaluating the application of IRIS game theoretic scheduler for use in scheduling airport security operations. TSA has begun to evaluate application of IRIS at the Pittsburgh International Airport and LAX with the Phase 1 currently operational.
