Node Capture Games: A Game Theoretic Approach to Modeling and Mitigating Node Capture Attacks

  • Tamara Bonaci
  • Linda Bushnell
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7037)


Unattended wireless sensor networks are susceptible to node capture attacks, where the adversary physically compromises a node, creates functional copies (clones) of it and deploys such clones back into the network, in order to impact the network’s functionality. In the absence of a centralized authority, distributed clone detection methods have been developed to mitigate this attack. In this paper, we show that the node capture attack and the network response can be modeled as a simultaneous, noncooperative, two-player game. In developing the game-theoretic framework, we consider a deterministic, linear dynamical model of the attack, as well as a general, stochastic model. For the deterministic model, we develop three games, all of which have quadratic utility for the valid network, whereas the adversary’s utility depends on the assumptions about ist abilities. For the stochastic model, we develop a game with convex utility functions. For each game, we prove the existence of a pure strategy Nash Equilibrium and present an efficient way of solving the game. These equilibria can then be used in choosing the appropriate parameters for detecting and responding to the attack. Simulations are provided to illustrate our approach.


Node Capture Attack Distributed Clone Detection Methods Noncooperative Games Convex Program 


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  1. 1.
    Andreson, B.D.O., Moore, J.B.: Optimal control: Linear Quadratic Methods. Dover Publications (2007)Google Scholar
  2. 2.
    Bertsekas, D.P., Gallager, R.: Data networks, 2nd edn. Prentice-Hall (1992)Google Scholar
  3. 3.
    Bonaci, T., Bushnell, L., Poovendran, R.: Node capture attacks in wireless sensor networks: A system theoretic approach. In: Proc. of the 49th IEEE Control and Desicion Conference, pp. 6765–6772 (2010)Google Scholar
  4. 4.
    Boyd, S., Vandenberghe, L.: Convex Optimization. Cambridge University Press (2004)Google Scholar
  5. 5.
    Conti, M., Di Pietro, R., Mancini, L.V., Mei, A.: A randomized, efficient, and distributed protocol for the detection of node replication attacks in wireless sensor networks. In: Proc. of the 8th ACM International Symposium on Mobile Ad Hoc Networking and Computing, pp. 80–89 (2007)Google Scholar
  6. 6.
    Eschenauer, L., Gligor, V.D.: A key-management scheme for distributed sensor networks. In: Proc. of the 9th ACM Conference on Computer and Communications Security, pp. 41–47 (2002)Google Scholar
  7. 7.
    Lazos, L., Poovendran, R.: SeRLoc: Robust localization for wireless sensor networks. ACM Trans. on Sensor Networks 1(1), 73–100 (2005)CrossRefGoogle Scholar
  8. 8.
    Li, Z., Gong, G.: Randomly directed exploration: An efficient node clone detection protocol in wireless sensor networks. In: Proc. of the 6th International IEEE Conference on Mobile Adhoc and Sensor Systems, pp. 1030–1035 (2009)Google Scholar
  9. 9.
    Parno, B., Perrig, A., Gligor, V.D.: Distributed detection of node replication attacks in sensor networks. In: Proc. of the IEEE Symposium on Security and Privacy, pp. 49–63 (2005)Google Scholar
  10. 10.
    Stinson, D.R.: Cryptography: Theory and Practice. Chapman & Hall/CRC (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Tamara Bonaci
    • 1
  • Linda Bushnell
    • 1
  1. 1.Department of Electrical EngineeringUniversity of WashingtonSeattleUSA

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