Game-theoretic analysis of node capture and cloning attack with multiple attackers in wireless sensor networks

Quanyan Zhu, Linda Bushnell, M Tamer Basar

Research output: Contribution to journalConference article

Abstract

Wireless sensor networks are subject to attacks such as node capture and cloning, where an attacker physically captures sensor nodes, replicates the nodes, which are deployed into the network, and proceeds to take over the network. In this paper, we develop models for such an attack when there are multiple attackers in a network, and formulate multi-player games to model the noncooperative strategic behavior between the attackers and the network. We consider two cases: a static case where the attackers' node capture rates are time-invariant and the network's clone detection/revocation rate is a linear function of the state, and a dynamic case where the rates are general functions of time. We characterize Nash equilibrium solutions for both cases and derive equilibrium strategies for the players. In the static case, we study both the single-attacker and the multi-attacker games within an optimization framework, provide conditions for the existence of Nash equilibria and characterize them in closed forms. In the dynamic case, we study the underlying multi-person differential game under an open-loop information structure and provide a set of conditions to characterize the open-loop Nash equilibrium. We show the equivalence of the Nash equilibrium for the multi-person game to the saddle-point equilibrium between the network and the attackers as a team. We illustrate our results with numerical examples.

Original languageEnglish (US)
Article number6426481
Pages (from-to)3404-3411
Number of pages8
JournalProceedings of the IEEE Conference on Decision and Control
DOIs
StatePublished - Dec 1 2012
Event51st IEEE Conference on Decision and Control, CDC 2012 - Maui, HI, United States
Duration: Dec 10 2012Dec 13 2012

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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