Resource-Aware Intrusion Detection in Infrastructure Networks: A Game-Theoretic Approach

2026-08-06

AI Summary

This study addresses the challenge posed by intelligent, path-adaptive attackers in resource-constrained infrastructure by modeling attacker-defender interactions as a graph-based security game subject to resource and false alarm constraints. Through rigorous analysis of the existence, structure, and computational complexity of Nash and Stackelberg equilibria under varying information structures, the work reveals how the attacker’s observational capability regarding defense strategies critically shapes equilibrium behavior. The paper introduces scalable solution algorithms tailored for both pure- and mixed-strategy settings and characterizes the ordinal relationship and coincidence conditions between the two equilibrium payoff profiles. Experimental results demonstrate that the proposed algorithms closely approximate full enumeration baselines on tractable instances while efficiently scaling to large, non-enumerable scenarios.

Abstract

Infrastructure networks increasingly rely on distributed sensing to detect intrusions before attackers reach valuable assets. Yet sensing devices, communication resources, and edge server capacity are limited, while intelligent attackers can adapt their routes to the deployed defense. Motivated by integrated sensing and communication (ISAC), we study how sensing and processing resources should be allocated under strategic interaction between a defender and an attacker. We formulate their interaction as a graph security game in which the defender deploys sensing actions under resource and false alarm constraints, while the attacker selects routes to valuable targets. We consider simultaneous play and settings in which the attacker observes either a pure defender configuration or a mixed defender strategy. Our analysis characterizes the existence, structure, and computational complexity of the Nash and Stackelberg equilibria, showing how the attacker's observation of the defense affects equilibrium behavior and when optimal strategies become difficult to compute. We develop algorithms that construct effective pure configurations and refine restricted games for mixed Nash and mixed Stackelberg play. On enumerable instances, their solutions have small mean normalized differences from fully enumerated references; the methods also apply when exhaustive strategy enumeration is impractical. We also identify conditions under which Nash and mixed Stackelberg payoffs are ordered or coincide.

Problem

• resource allocation
• intrusion detection
• infrastructure networks
• strategic attacker
• security game

Innovation

• game-theoretic security
• resource-aware intrusion detection
• graph security game
• Stackelberg equilibrium
• integrated sensing and communication (ISAC)