# Analysis of Complex Network Attack and Defense Game Strategies Under Uncertain Value Criterion

## TL;DR

This paper studies how attackers and defenders in network security make decisions when they value targets differently, offering practical strategies for uncertain situations.

## Contribution

The paper introduces the concept of 'advantage ranges' for attackers and defenders with differing value criteria in network games.

## Key findings

- Attackers and defenders have distinct 'advantage ranges' for value assessment based on network topology.
- Within advantage ranges, optimal strategies can be chosen without considering opponents' decisions.
- Outside these ranges, attackers can use small-sample detection to infer defender strategies probabilistically.

## Abstract

The study of attack–defense game decision making in critical infrastructure systems confronting intelligent adversaries, grounded in complex network theory, has emerged as a prominent topic in the field of network security. Most existing research centers on game-theoretic analysis under conditions of complete information and assumes that the attacker and defender share congruent criteria for evaluating target values. However, in reality, asymmetric value perception may lead to different evaluation criteria for both the offensive and defensive sides. This paper examines the game problem wherein the attacker and defender possess distinct target value evaluation criteria. The research findings reveal that both the attacker and defender have their own “advantage ranges” for value assessment, and topological heterogeneity is the reason for this phenomenon. Within their respective advantage ranges, the attacker or defender can adopt clear-cut strategies to secure optimal benefits—without needing to consider their opponents’ decisions. Outside these ranges, we explore how the attacker can leverage small-sample detection outcomes to probabilistically infer defenders’ strategies, and we further analyze the attackers’ preference strategy selections under varying acceptable security thresholds and penalty coefficients. The research results deliver more practical solutions for games involving uncertain value criteria.