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

TL;DR

This paper introduces a decision-dominant, game-theoretic security framework for 5G multi-domain military networks, enhancing zero-trust defenses against lateral movement and targeted cyber-attacks in complex battlefield environments.

Contribution

It presents a novel decision-dominant, meta-learning based approach for proactive security and zero-trust monitoring in 5G-enabled multi-domain military networks.

Findings

Effective thwarting of lateral movement by adversaries.

Enhanced zero-trust monitoring capabilities.

Robust defense in complex multi-domain environments.

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.