1st International Conference on Game Theory for Networks

Research Article

A game-theoretical approach to incentive design in collaborative intrusion detection networks

  • @INPROCEEDINGS{10.1109/GAMENETS.2009.5137424,
        author={Quanyan   Zhu,  and Carol Fung and Raouf Boutaba and Tamer  Basar},
        title={A game-theoretical approach to incentive design in collaborative intrusion detection networks},
        proceedings={1st International Conference on Game Theory for Networks},
        publisher={IEEE},
        proceedings_a={GAMENETS},
        year={2009},
        month={6},
        keywords={},
        doi={10.1109/GAMENETS.2009.5137424}
    }
    
  • Quanyan Zhu,
    Carol Fung
    Raouf Boutaba
    Tamer Basar
    Year: 2009
    A game-theoretical approach to incentive design in collaborative intrusion detection networks
    GAMENETS
    IEEE
    DOI: 10.1109/GAMENETS.2009.5137424
Quanyan Zhu, 1,*, Carol Fung2,*, Raouf Boutaba2,*, Tamer Basar1,*
  • 1: Department of Electrical and Computer Engineering and the Coordinated Science Laboratory, University of Illinois at Urbana Champaign USA.
  • 2: Cheriton School of Computer Science at University of Waterloo, Ontario, Canada.
*Contact email: zhu31@decision.csl.uiuc.edu, j22fung@cs.uwaterloo.ca, rboutabag@cs.uwaterloo.ca, tbasarg@decision.csl.uiuc.edu

Abstract

Traditional intrusion detection systems (IDSs) work in isolation and may be easily compromised by new threats. An intrusion detection network (IDN) is a collaborative IDS network intended to overcome this weakness by allowing IDS peers to share collective knowledge and experience, hence improve the overall accuracy of intrusion assessment. In this work, we design an incentive model based on trust management by using game theory for peers to collaborate truthfully without free-riding in an IDN environment. We show the existence and uniqueness of a Nash equilibrium under which peers can communicate in an incentive compatible manner. Using duality of the problem, we develop an iterative algorithm that converges geometrically to the equilibrium. Our numerical experiments and discrete event simulation demonstrate the convergence to the Nash equilibrium and the incentives of the resource allocation design.