Modeling Resources Allocation in Attacker-Defender Games with "Warm Up" CSF.

Like many other engineering investments, the attacker's and defender's investments may have limited impact without initial capital to "warm up" the systems. This article studies such "warm up" effects on both the attack and defense equilibrium strategies in a sequential-move game model by developing a class of novel and more realistic contest success functions. We first solve a single-target attacker-defender game analytically and provide numerical solutions to a multiple-target case. We compare the results of the models with and without consideration of the investment "warm up" effects, and find that the defender would suffer higher expected damage, and either underestimate the attacker effort or waste defense investment if the defender falsely believes that no investment "warm up" effects exist. We illustrate the model results with real data, and compare the results of the models with and without consideration of the correlation between the "warm up" threshold and the investment effectiveness. Interestingly, we find that the defender is suggested to give up defending all the targets when the attack or the defense "warm up" thresholds are sufficiently high. This article provides new insights and suggestions on policy implications for homeland security resource allocation.

[1]  Jun Zhuang,et al.  Impacts of Subsidized Security on Stability and Total Social Costs of Equilibrium Solutions in an N-Player Game with Errors , 2010 .

[2]  Kjell Hausken,et al.  Defending Against a Stockpiling Terrorist , 2011 .

[3]  Jun Zhuang,et al.  Modeling Arbitrary Layers of Continuous‐Level Defenses in Facing with Strategic Attackers , 2011, Risk analysis : an official publication of the Society for Risk Analysis.

[4]  Jun Zhuang,et al.  Modelling ‘contracts’ between a terrorist group and a government in a sequential game , 2012, J. Oper. Res. Soc..

[5]  M. Naceur Azaiez,et al.  Optimal resource allocation for security in reliability systems , 2007, Eur. J. Oper. Res..

[6]  Xiaojun Shan,et al.  Hybrid defensive resource allocations in the face of partially strategic attackers in a sequential defender-attacker game , 2013, Eur. J. Oper. Res..

[7]  Vicki M. Bier,et al.  Balancing Terrorism and Natural Disasters - Defensive Strategy with Endogenous Attacker Effort , 2007, Oper. Res..

[8]  Oguzhan Alagöz,et al.  Modeling secrecy and deception in a multiple-period attacker-defender signaling game , 2010, Eur. J. Oper. Res..

[9]  Todd Sandler,et al.  The calculus of dissent: An analysis of terrorists' choice of targets , 1988, Synthese.

[10]  J. Hirshleifer Conflict and rent-seeking success functions: Ratio vs. difference models of relative success , 1989 .

[11]  S. Skaperdas Contest success functions , 1996 .

[12]  Harvey E. Lapan,et al.  To Bargain or Not to Bargain: That is the Question , 1988 .

[13]  Kjell Hausken Strategic defense and attack for reliability systems , 2008, Reliab. Eng. Syst. Saf..

[14]  K. Hausken Game Theoretic Analysis of Standby Systems , 2012 .

[15]  T. Sandler,et al.  Terrorism & Game Theory , 2003 .

[16]  Jun Zhuang,et al.  Robust Allocation of a Defensive Budget Considering an Attacker's Private Information , 2012, Risk analysis : an official publication of the Society for Risk Analysis.

[17]  Jun Zhuang,et al.  Robustness of Optimal Defensive Resource Allocations in the Face of Less Fully Rational Attacker , 2009 .

[18]  P. Douglas,et al.  A theory of production , 1928 .

[19]  Jun Zhuang,et al.  Cost of Equity in Homeland Security Resource Allocation in the Face of a Strategic Attacker , 2013, Risk analysis : an official publication of the Society for Risk Analysis.

[20]  Larry Samuelson,et al.  Choosing What to Protect: Strategic Defensive Allocation Against an Unknown Attacker , 2005 .

[21]  Jun Zhuang,et al.  Modeling a Multitarget Attacker-Defender Game with Budget Constraints , 2017, Decis. Anal..

[22]  Tito Homem-de-Mello,et al.  Risk-adjusted budget allocation models with application in homeland security , 2011 .

[23]  Rae Zimmerman,et al.  Optimal Resource Allocation for Defense of Targets Based on Differing Measures of Attractiveness , 2008, Risk analysis : an official publication of the Society for Risk Analysis.

[24]  Vicki M. Bier,et al.  Secrecy in Defensive Allocations as a Strategy for Achieving More Cost-Effec tive Att acker Dett errence , 2009 .

[25]  V. Bier,et al.  SECRECY AND DECEPTION AT EQUILIBRIUM, WITH APPLICATIONS TO ANTI‐TERRORISM RESOURCE ALLOCATION , 2011 .

[26]  Henry H. Willis,et al.  Estimating Terrorism Risk , 2002 .

[27]  Chen Wang,et al.  Target-Hardening Decisions Based on Uncertain Multiattribute Terrorist Utility , 2011, Decis. Anal..

[28]  V. Bier,et al.  Reasons for Secrecy and Deception in Homeland‐Security Resource Allocation , 2010, Risk analysis : an official publication of the Society for Risk Analysis.

[29]  Kjell Hausken,et al.  The timing and deterrence of terrorist attacks due to exogenous dynamics , 2012, J. Oper. Res. Soc..

[30]  Kjell Hausken,et al.  Defending Against Terrorism, Natural Disaster, and All Hazards , 2009 .