Decision-Dominant Strategic Defense Against Lateral Movement for 5G Zero-Trust Multi-Domain Networks

Tao Li, Yunian Pan, Quanyan Zhu*

*Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 12 - Chapter in an edited book (Author)peer-review

2 Citations (Scopus)

Abstract

Multi-domain warfare is a military doctrine that leverages capabilities from different domains, including air, land, sea, space, and cyberspace, to create a highly interconnected battle network that is difficult for adversaries to disrupt or defeat. However, the adoption of 5G technologies on battlefields presents new vulnerabilities due to the complexity of interconnections and the diversity of software, hardware, and devices from different supply chains. Therefore, establishing a zero-trust architecture for 5G-enabled networks is crucial for continuous monitoring and fast data analytics to protect against targeted attacks. To address these challenges, we propose a proactive end-to-end security scheme that utilizes a 5G satellite-guided air-ground network. Our approach incorporates a decision-dominant learning-based method that can thwart the lateral movement of adversaries targeting critical assets on the battlefield before they can conduct reconnaissance or gain necessary access or credentials. We demonstrate the effectiveness of our game-theoretic design, which uses a meta-learning framework to enable zero-trust monitoring and decision-dominant defense against attackers in emerging multi-domain battlefield networks. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Original languageEnglish
Title of host publicationNetwork Security Empowered by Artificial Intelligence
EditorsYingying Chen, Jie Wu, Paul Yu, Xiaogang Wang
Place of PublicationCham
PublisherSpringer 
Pages25-76
Number of pages52
ISBN (Electronic)978-3-031-53510-9
ISBN (Print)978-3-031-53509-3
DOIs
Publication statusPublished - 2024
Externally publishedYes

Publication series

NameAdvances in Information Security
Volume107
ISSN (Print)1568-2633
ISSN (Electronic)2512-2193

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