A Blockchain-Enabled Decentralized Zero-Trust Architecture for Anomaly Detection in Satellite Networks via Post-Quantum Cryptography and Federated Learning

Sridhar Varadala and Hao Xu ()
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Sridhar Varadala: Department of Electrical and Biomedical Engineering, University of Nevada, Reno, NV 89557, USA
Hao Xu: Department of Electrical and Biomedical Engineering, University of Nevada, Reno, NV 89557, USA

Future Internet, 2025, vol. 17, issue 11, 1-22

Abstract: The rapid expansion of satellite networks for advanced communication and space exploration has ensured that robust cybersecurity for inter-satellite links has become a critical challenge. Traditional security models rely on centralized trust authorities, and node-specific protections are no longer sufficient, particularly when system failures or attacks affect groups of satellites or agent clusters. To address this problem, we propose a blockchain-enabled decentralized zero-trust model based on post-quantum cryptography (BEDZTM-PQC) to improve the security of satellite communications via continuous authentication and anomaly detection. This model introduces a group-based security framework, where satellite teams operate under a zero-trust architecture (ZTA) enforced by blockchain smart contracts and threshold cryptographic mechanisms. Each group shares the responsibility for local anomaly detection and policy enforcement while maintaining decentralized coordination through hierarchical federated learning, allowing for collaborative model training without centralizing sensitive telemetry data. A post-quantum cryptography (PQC) algorithm is employed for future-proof communication and authentication protocols against quantum computing threats. Furthermore, the system enhances network reliability by incorporating redundant communication channels, consensus-based anomaly validation, and group trust scoring, thus eliminating single points of failure at both the node and team levels. The proposed BEDZTM-PQC is implemented in MATLAB, and its performance is evaluated using key metrics, including accuracy, latency, security robustness, trust management, anomaly detection accuracy, performance scalability, and security rate with respect to different numbers of input satellite users.

Keywords: anomaly detection; blockchain ledger; continuous authentication; decentralized zero trust model; post-quantum cryptography and federated learning (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2025
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