Protecting Moving Targets with Multiple Mobile Resources

Abstract

In recent years, Stackelberg Security Games have been successfully applied to solve resource allocation and scheduling problems in several security domains. However, previous work has mostly assumed that the targets are stationary relative to the defender and the attacker, leading to discrete game models with finite numbers of pure strategies. This paper in contrast focuses on protecting mobile targets that leads to a continuous set of strategies for the players. The problem is motivated by several real-world domains including protecting ferries with escort boats and protecting refugee supply lines. Our contributions include: (i) A new game model for multiple mobile defender resources and moving targets with a discretized strategy space for the defender and a continuous strategy space for the attacker.(ii) An efficient linear-programming-based solution that uses a compact representation for the defender's mixed strategy, while accurately modeling the attacker's continuous strategy using a novel sub-interval analysis method. (iii) Discussion and analysis of multiple heuristic methods for equilibrium refinement to improve robustness of defender's mixed strategy. (iv) Discussion of approaches to sample actual defender schedules from the defender's mixed strategy. (iv) Detailed experimental analysis of our algorithms in the ferry protection domain.

Computational Game Theory for Security and Sustainability

“…We developed a game-theoretic system for scheduling escort boat patrols to protect ferries, and this has been deployed at the Staten Island Ferry since 2013 [10] (Fig. 3).…”

“…However, this approach is unable to deal with complex constraints on the defender resources [24]. Nevertheless, we have recently been able to use this approach for certain patrolling domains, including fare-enforcement patrols in urban transit systems [43] and boat patrols for protecting ferries [10]. In these domains a pure strategy is a patrol of a certain time duration over a set of locations, and the number of such pure strategies grow exponentially in the time duration.…”

“…These algorithms have led to some initial successes in this challenging problem arena, leading to advances over previous approaches in security scheduling and allocation, e.g., by addressing key weaknesses of predictability of human schedulers. These algorithms are now deployed in multiple applications: Armor has been deployed at the Los Angeles International Airport (LAX) since 2007 to randomize checkpoints on the roadways entering the airport and canine patrol routes within the airport terminals [17] Iris, a game-theoretic scheduler for randomized deployment of the US Federal Air Marshals (FAMS) requiring significant scaleup in underlying algorithms, has been in use since 2009 [17]; Protect, which schedules the US Coast Guard's randomized patrolling of ports using a new set of algorithms based on modeling bounded-rational human attackers, has been deployed in the port of Boston since April 2011 and is in use at the port of New York since February 2012 [34], and is headed for nationwide deployment; another application for deploying escort boats to protect ferries has been deployed by the US Coast Guard since April 2013 [10]; Guards is under evaluation for national deployment by the US Transportation Security Administration (TSA) [32], and Trusts [43] has been evaluated in field trials by the Los Angeles Sheriffs Department (LASD) in the LA Metro system and a nation-wide deployment is now being evaluated at TSA. These initial successes point the way to major future applications in a wide range of security domains; with major research challenges in scaling up our game-theoretic algorithms, in addressing human adversaries' bounded rationality and uncertainties in action execution and observation, as well as in multiagent learning.…”

Moving From ‘How to go There?’ to ‘Where to go?’: Towards Increased Autonomy of Mobile Robots

“…It moves, repeatedly monitoring different portions of the environment. The problem of patrolling environments with autonomous mobile robots has attracted the attention of many researchers both within the Autonomous Robotics and the Multiagent Systems communities [2,14]. It can be considered as an instance of a general class of problems related to surveillance and security [19] and can be generalized from detecting intruders to detecting any kind of threats.…”

From Battlefields to Elections: Winning Strategies of Blotto and Auditing Games

“…Many different variants of security games, targeting different applications (e.g., protecting a set of nodes in a graph, scheduling a set of patrols in space and time, etc.) have been considered in the literature [5,11,36,8,20].…”