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This study introduces two greedy heuristic strategies for cyber war games, optimizing resource use for attackers and defenders in dynamic, distributed networks. These methods aim for efficient wins by considering node resources and influence.

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Area of Science:

  • Cybersecurity
  • Game Theory
  • Network Science

Background:

  • Cyber war games involve distributed networks with resource constraints and high dynamics.
  • Optimizing strategies for attackers and defenders to achieve goals with minimal effort is crucial.
  • Network dynamics (mobility, failure, resource depletion) make optimal strategy determination NP-complete.

Purpose of the Study:

  • To develop and evaluate heuristic strategies for attackers and defenders in cyber war games.
  • To minimize resource consumption while achieving system goal states (winning conditions).
  • To address the complexity arising from dynamic and resource-constrained networks.

Main Methods:

  • Proposed two greedy heuristic strategies based on node resource level and k-hop reachability influence.
  • Analyzed algorithm complexity and optimality against optimal solutions in small-scale static networks.
  • Conducted extensive experiments on large-scale temporal networks with varying temporality and density.

Main Results:

  • Demonstrated the performance of heuristic strategies under diverse attacker/defender scenarios.
  • Evaluated strategies based on win probability, resource consumption, and system vulnerability.
  • Compared heuristic performance against optimal solutions in controlled environments.

Conclusions:

  • Heuristic strategies offer viable solutions for complex cyber war game scenarios.
  • Node characteristics (resources, influence) are key factors in developing effective strategies.
  • The proposed methods provide practical approaches for optimizing cyber warfare in dynamic networks.