A Multi-Resolution Dynamic Game Framework for Cross-Echelon Decision-Making in Cyber Warfare

TL;DR

This paper introduces a multi-resolution dynamic game framework for cyber warfare decision-making, enabling scalable reasoning across tactical and strategic levels to improve defense strategies in complex cyber environments.

Contribution

It presents a novel multi-resolution modeling approach combining high-resolution game trees and lower-resolution Markov games for cross-echelon cyber defense planning.

Findings

Framework effectively models multi-level cyber interactions

Zoom-in and zoom-out operations enable scalable analysis

Case study shows improved defender strategic advantage

Abstract

Cyber warfare has become a critical dimension of modern conflict, driven by society's increasing dependence on interconnected digital and physical infrastructure. Effective cyber defense often requires decision-making at different echelons, where the tactical layer focuses on detailed actions such as techniques, tactics, and procedures, while the strategic layer addresses long-term objectives and coordinated planning. Modeling these interactions at different echelons remains challenging due to the dynamic, large-scale, and interdependent nature of cyber environments. To address this, we propose a multi-resolution dynamic game framework in which the tactical layer captures fine-grained interactions using high-resolution extensive-form game trees, while the strategic layer is modeled as a Markov game defined over lower-resolution states abstracted from those game trees. This framework supports scalable reasoning and planning across different levels of abstraction through zoom-in and zoom-out operations that adjust the granularity of the modeling based on operational needs. A case study demonstrates how the framework works and its effectiveness in improving the defender's strategic advantage.