Network Security under Heterogeneous Cyber-Risk Profiles and Contagion

2026-01-23

AI Summary

This study addresses the challenge of optimizing defensive resource allocation in networks characterized by heterogeneous node values and risk contagion. The authors propose an integrated framework that combines security game theory with epidemic dynamics, incorporating asymmetric valuations of nodes by attackers and defenders. By leveraging weighted network metrics and risk-path analysis, they develop a novel risk measure that explicitly accounts for how propagation pathways shape optimal defense strategies. Through numerical optimization and extensive simulations across diverse network topologies, the work identifies cost–risk efficient frontiers, uncovers strategic patterns in resource allocation, and reveals network deception effects. These findings offer actionable insights for enhancing the resilience of critical digital infrastructure systems.

Technology Category

• Game Theory and Economic Paradigms: Cooperative Game Theory
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Reasoning under Uncertainty: Stochastic Optimization

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Security and Privacy: Large-scale security measurements
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Cyber risk has become a critical financial threat in today's interconnected digital economy. This paper introduces a cyber-risk management framework for networked digital systems that combines the strategic behavior of players with contagion dynamics within a security game. We address the problem of optimally allocating cybersecurity resources across a network, focusing on the heterogeneous valuations of nodes by attackers and defenders, some areas may be of high interest to the attacker, while others are prioritized by the defender. We explore how this asymmetry drives attack and defense strategies and shapes the system's overall resilience. We extend a method to determine optimal resource allocation based on simple network metrics weighted by the defender's and attacker's risk profiles. We further propose risk measures based on contagion paths and analyze how propagation dynamics influence optimal defense strategies. Numerical experiments explore risk versus cost efficient frontiers varying network topologies and risk profiles, revealing patterns of resource allocation and cyber deception effects. These findings provide actionable insights for designing resilient digital infrastructures and mitigating systemic cyber risk.

Problem

• cyber-risk
• heterogeneous risk profiles
• contagion dynamics
• resource allocation
• network security

Innovation

• cyber-risk heterogeneity
• security game
• contagion dynamics
• optimal resource allocation
• cyber deception