Blockchain-Enabled Routing for Zero-Trust Low-Altitude Intelligent Networks

2026-02-27

AI Summary

This work addresses the challenges of routing security and reliability in low-altitude intelligent networks, where high UAV mobility and distributed topology introduce significant vulnerabilities. To this end, the paper proposes a novel secure routing mechanism that integrates zero-trust architecture with blockchain technology. UAV identities and dynamic access are managed via software-defined perimeters, while routing optimization is formulated as a decentralized partially observable Markov decision process. A multi-agent double deep Q-network algorithm is developed, incorporating soft hierarchy and prioritized experience replay. This approach represents the first synergistic application of zero-trust principles and blockchain in low-altitude networks, achieving substantial improvements: compared to baseline schemes, it reduces end-to-end latency by 59%, increases transmission success rate by 29%, and enables faster, more robust identification of low-trust nodes.

Technology Category

• Planning, Routing, and Scheduling: Planning under Uncertainty
• Multiagent Systems: Multiagent Systems under Uncertainty
• Intelligent Robots: Learning & Optimization for ROB

Application Category

• Security and Privacy: Blockchains and distributed ledgers
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Due to the scalability and portability, low-altitude intelligent networks (LAINs) are essential in various fields such as surveillance and disaster rescue. However, in LAINs, unmanned aerial vehicles (UAVs) are characterized by the distributed topology and high mobility, thus vulnerable to security threats, which may degrade routing performances for data transmissions. Hence, how to ensure the routing stability and security of LAINs is challenging. In this paper, we focus on the routing with multiple UAV clusters in LAINs. To minimize the damage caused by potential threats, we present the zero-trust architecture with the software-defined perimeter and blockchain techniques to manage the identify and mobility of UAVs. Besides, we formulate the routing problem to optimize the end-to-end (E2E) delay and transmission success ratio (TSR) simultaneously, which is an integer nonlinear programming problem and intractable to solve. Therefore, we reformulate the problem into a decentralized partially observable Markov decision process. We design the multi-agent double deep Q-network-based routing algorithms to solve the problem, empowered by the soft-hierarchical experience replay buffer and prioritized experience replay mechanisms. Finally, extensive simulations are conducted and the numerical results demonstrate that the proposed framework reduces the average E2E delay by 59\% and improves the TSR by 29\% on average compared to benchmarks, while simultaneously enabling faster and more robust identification of low-trust UAVs.

Problem

• low-altitude intelligent networks
• unmanned aerial vehicles
• routing security
• zero-trust architecture
• network stability

Innovation

• blockchain-enabled routing
• zero-trust architecture
• multi-agent reinforcement learning
• low-altitude intelligent networks
• decentralized POMDP