Attacker Detection Game in Wireless Networks with Channel Uncertainty

Abstract

Identification and isolation of attackers in a distributed system is a challenging problem. This problem is even more aggravated in a wireless network because the unreliable channel makes the actions of the users (nodes) hidden from each other. Therefore, legitimate users can only construct a belief about a potential attacker through monitoring and observation. In this paper, we use game theory to study the interactions between regular and attacker nodes in a wireless network. We model the attacker node detection process as a Bayesian game with imperfect information and show that a mixed strategy perfect Bayesian Nash Equilibrium is attainable. Further, we show how an attacker node can construct a nested belief system to predict the belief held by a regular node. By employing the nested belief system, a Markov Perfect Bayes-Nash Equilibrium is reached and the equilibrium postpones the detection of the attacker node. Simulation results and their discussions are provided to illustrate the properties of the derived equilibria.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2010
Accession Number
ADA527714

Entities

People

  • Kevin Kwiat
  • Mainak Chatterjee
  • Wenjing Wang

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Cyber
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Camouflage
  • Computer Science
  • Detection
  • Electrical Engineering
  • Engineering
  • Equations
  • False Alarms
  • Game Theory
  • Intrusion Detection
  • Monitoring
  • Networks
  • Observation
  • Simulations
  • Uncertainty
  • Wireless Networks
  • Zero-Sum Games

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Game Theory.
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference