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Adversarial Behavior in Network Games

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  • Anil Chorppath

  • Tansu Alpcan

  • Holger Boche

Abstract

This paper studies the effects of and countermeasures against adversarial behavior in network resource allocation mechanisms such as auctions and pricing schemes. It models the heterogeneous behavior of users, which ranges from altruistic to selfish and to malicious, within the analytical framework of game theory. A mechanism design approach is adopted to quantify the effect of adversarial behavior, which ranges from extreme selfishness to destructive maliciousness. First, the well-known result on the Vicrey–Clarke–Groves (VCG) mechanism losing its efficiency property in the presence of malicious users is extended to the case of divisible resource allocation to motivate the need to quantify the effect of malicious behavior. Then, the Price of Malice of the VCG mechanism and of some other network mechanisms are derived. In this context, the dynamics and convergence properties of an iterative distributed pricing algorithm are analyzed. The resistance of a mechanism to collusions is investigated next, and the effect of collusion of some malicious users is quantified. Subsequently, the assumption that the malicious user has information about the utility function of selfish users is relaxed, and a regression-based iterative learning scheme is presented and applied to both pricing and auction mechanisms. Differentiated pricing as a method to counter adversarial behaviors is proposed and briefly discussed. The results obtained are illustrated with numerical examples and simulations. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Anil Chorppath & Tansu Alpcan & Holger Boche, 2015. "Adversarial Behavior in Network Games," Dynamic Games and Applications, Springer, vol. 5(1), pages 26-64, March.
    • Handle: RePEc:spr:dyngam:v:5:y:2015:i:1:p:26-64
    DOI: 10.1007/s13235-014-0120-4
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    References listed on IDEAS

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    1. Hervé Moulin & Scott Shenker, 2001. "Strategyproof sharing of submodular costs:budget balance versus efficiency," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 18(3), pages 511-533.
    2. Chen, Jing & Micali, Silvio, 2012. "Collusive dominant-strategy truthfulness," Journal of Economic Theory, Elsevier, vol. 147(3), pages 1300-1312.
    3. Morgan John & Steiglitz Ken & Reis George, 2003. "The Spite Motive and Equilibrium Behavior in Auctions," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 2(1), pages 1-25, April.
    4. William Vickrey, 1961. "Counterspeculation, Auctions, And Competitive Sealed Tenders," Journal of Finance, American Finance Association, vol. 16(1), pages 8-37, March.
    5. John C. Harsanyi, 1967. "Games with Incomplete Information Played by "Bayesian" Players, I-III Part I. The Basic Model," Management Science, INFORMS, vol. 14(3), pages 159-182, November.
    6. Robert J. Aumann, 2025. "Correlated Equilibrium as an Expression of Bayesian Rationality," World Scientific Book Chapters, in: SELECTED CONTRIBUTIONS TO GAME THEORY, chapter 7, pages 175-200, World Scientific Publishing Co. Pte. Ltd..
    7. Gaurab Aryal & Maria F. Gabrielli, 2012. "Estimating Revenue Under Collusion-Proof Auctions," ANU Working Papers in Economics and Econometrics 2012-597, Australian National University, College of Business and Economics, School of Economics.
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