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

Fuente: arXiv
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Autori principali: Yang, Ya-Ting, Zhu, Quanyan
Natura: Preprint
Pubblicazione: 2025
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author Yang, Ya-Ting
Zhu, Quanyan
author_facet Yang, Ya-Ting
Zhu, Quanyan
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2507_03021
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A Multi-Resolution Dynamic Game Framework for Cross-Echelon Decision-Making in Cyber Warfare
Yang, Ya-Ting
Zhu, Quanyan
Cryptography and Security
Computer Science and Game Theory
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.
title A Multi-Resolution Dynamic Game Framework for Cross-Echelon Decision-Making in Cyber Warfare
topic Cryptography and Security
Computer Science and Game Theory
url https://arxiv.org/abs/2507.03021