Modelling and Research on Intuitionistic Fuzzy Goal-Based Attack and Defence Game for Infrastructure Networks.

Area of Science:

• Network security
• Game theory
• Infrastructure protection

Background:

• Existing network attack and defense game studies often overlook subjective uncertainties from attackers and defenders.
• Infrastructure networks like power grids and transportation systems require robust protection strategies.
• Understanding attacker and defender decision-making under uncertainty is crucial for effective network security.

Purpose of the Study:

• To develop an intuitionistic fuzzy goal-based attack and defense game model for infrastructure networks.
• To incorporate subjective factors like expectation value, rejection value, and hesitation degree into the game model.
• To analyze network security strategies considering the maximum connectivity slice size as a key performance index.

Main Methods:

• Constructed an intuitionistic fuzzy two-player, zero-sum game model for infrastructure network attack and defense.
• Converted the fuzzy game model into a linear programming problem for computational analysis.
• Evaluated the model's applicability and feasibility through single-round and multi-round repeated game scenarios.

Main Results:

• Attackers tend to target less prominent network nodes (neutrality and median) rather than highly important ones.
• Defenders prioritize protecting the most critical nodes to maintain overall network performance.
• The proposed intuitionistic fuzzy game model effectively captures and analyzes network attack and defense dynamics under uncertainty.

Conclusions:

• The developed intuitionistic fuzzy game model provides a novel approach to studying network attack and defense strategies.
• Accounting for subjective decision preferences enhances the realism and applicability of network security game models.
• The findings offer valuable insights for optimizing defensive strategies in critical infrastructure networks.