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Quantifying Adversary Capabilities to Inform Defensive Resource Allocation.

Chen Wang1, Vicki M Bier2

  • 1Department of Industrial Engineering, Tsinghua University, Beijing 100084, China.

Risk Analysis : an Official Publication of the Society for Risk Analysis
|May 2, 2015
PubMed
Summary
This summary is machine-generated.

This study introduces a Bayesian Stackelberg game to optimize defensive strategies by considering attacker intent and capabilities. Accurate attacker capability assessment is crucial, potentially outweighing the need for precise intent evaluation.

Keywords:
Adversary capabilityStackelberg gamehomeland securityuncertainty

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Area of Science:

  • Cybersecurity
  • Game Theory
  • Economics

Background:

  • Optimal defensive strategies are critical in cybersecurity.
  • Understanding attacker motivations and capabilities is complex.
  • Existing models often struggle to integrate these factors effectively.

Purpose of the Study:

  • To develop a Bayesian Stackelberg game model for analyzing attacker intent and capabilities.
  • To integrate economic contest success functions into security game analysis.
  • To determine the impact of attacker characteristics on optimal defense investments.

Main Methods:

  • Formulated a Bayesian Stackelberg game.
  • Incorporated contest success functions to model attack attribution.
  • Analyzed the interplay between defender investment and attacker attributes.
  • Utilized a two-target scenario for empirical evaluation.

Main Results:

  • The model successfully analyzes joint effects of attacker intent and capability on defense.
  • Contest success functions effectively distinguish capability-driven success from chance.
  • In scenarios with poor capability estimates, precise intent assessment may be less critical.

Conclusions:

  • The proposed Bayesian Stackelberg game offers a robust framework for cybersecurity defense.
  • Attacker capability is a significant factor in determining optimal defensive resource allocation.
  • The model provides insights into strategic decision-making under uncertainty in cyber defense.