Strategic Security Placement in Network Domains with Applications to Transit Security

Deterministic placement of security personnel creates serious vulnerabilities for any organization attempting to prevent intrusion. Recent work in use at the Los Angeles International Airport (LAX) and in progress with the United States Federal Air Marshal Service (FAMS) has applied game-theoretic analysis to the problem by modeling it as a Stackelberg game wherein security forces are the leaders that commit to a strategy that is observed and countered by attackers. In this work, we explore efficient techniques for performing the same analysis on games with a graph structure, wherein an attacker must follow a path from an entry point to a target. If we frame these problems in the straightforward manner with leader actions being sets of edges that can be guarded and follower actions being paths from entry to targets, the size of the game increases exponentially, quickly reaching memory limitations when using general Stackelberg solvers. In this work, we propose a novel linear program that is able to solve this type of problem efficiently. While it provides exact solutions for games where only one checkpoint is allowed, it is an approximation in the general case. Finally, we compare the performance of this and other methods by generating optimal policies for the Seoul Metropolitan Subway in Seoul, South Korea.

[1]  David P. Morton,et al.  Stochastic Network Interdiction , 1998, Oper. Res..

[2]  Mikel Buesa,et al.  The Economic Cost of March 11: Measuring the Direct Economic Cost of the Terrorist Attack on March 11, 2004 in Madrid , 2007 .

[3]  James Aspnes,et al.  Inoculation strategies for victims of viruses and the sum-of-squares partition problem , 2005, SODA '05.

[4]  R. Kevin Wood,et al.  Deterministic network interdiction , 1993 .

[5]  H. Stackelberg,et al.  Marktform und Gleichgewicht , 1935 .

[6]  Sarit Kraus,et al.  Playing games for security: an efficient exact algorithm for solving Bayesian Stackelberg games , 2008, AAMAS.

[7]  R. Kevin Wood,et al.  Shortest‐path network interdiction , 2002, Networks.

[8]  B. Stengel,et al.  Leadership with commitment to mixed strategies , 2004 .

[9]  Michael L. Littman,et al.  Graphical Models for Game Theory , 2001, UAI.

[10]  Milind Tambe,et al.  Security and Game Theory: IRIS – A Tool for Strategic Security Allocation in Transportation Networks , 2011, AAMAS 2011.

[11]  Manish Jain,et al.  Computing optimal randomized resource allocations for massive security games , 2009, AAMAS 2009.

[12]  Gerald G. Brown,et al.  Defending Critical Infrastructure , 2006, Interfaces.

[13]  Rudolf Avenhaus,et al.  Inspection Games , 2009, Encyclopedia of Complexity and Systems Science.

[14]  Alan Washburn,et al.  Two-Person Zero-Sum Games for Network Interdiction , 1995, Oper. Res..

[15]  Sarit Kraus,et al.  Deployed ARMOR protection: the application of a game theoretic model for security at the Los Angeles International Airport , 2008, AAMAS 2008.

[16]  M. Mitzenmacher,et al.  Probability and Computing: Events and Probability , 2005 .

[17]  Micah Adler,et al.  Randomized Pursuit-Evasion In Graphs , 2003, Comb. Probab. Comput..

[18]  Michael Mitzenmacher,et al.  Probability And Computing , 2005 .

[19]  L. Goddard,et al.  Operations Research (OR) , 2007 .

[20]  E. Todeva Networks , 2007 .