Evidence map›Paper›PMID 42086711›Full record

ArticleScientific reports2026

TwinGuard-Sec: a federated blockchain-enabled AI framework for standardized security and privacy in cross-domain digital twin ecosystems over 6G.

Mrim M Alnfiai, Reemiah Muneer Alotaibi, Faiz Abdullah Alotaibi

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Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Mrim M AlnfiaiDepartment of Information Technology, College of Computers and Information Technology, Taif University, Taif, P.O. Box 11099, 21944, Taif, Saudi Arabia. m.alnofiee@tu.edu.sa.
Reemiah Muneer AlotaibiCollege of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia.
Faiz Abdullah AlotaibiDepartment of Information Science, College of Humanities and Social Sciences, King Saud University, Riyadh, Saudi Arabia.

Funding

Taif University TU-DSPP-2024-41
6 · The paper itself

Abstract

The fast rate of cross-domain Digital Twins (DT) ecosystem growth in 6G-based scenarios poses unresolved security and privacy issues into the scope of existing frameworks. This study examines the inherent constraints of existing methods and presents TwinGuard-Sec, a new federated blockchain-based AI system expressly aimed at providing a set of standardized security and privacy of data in a heterogeneous realm of DT. The methodology comprises a dual-layered systematic architectural framework, comprising an AI-governed threat intelligence unit and zero-knowledge identity verifications and a distributed ledger technology layer that is domain-interoperable with lightweight consensus algorithms ensuring synchronous operation in real time. The framework fills three essential gaps in research including: absence of standardized cross-domain security protocols, inadequate privacy preserving mechanisms applied to sensitive inter-organizational data sharing and lack of scalable consensus algorithms to be used in DT-specific needs. We show on the rigorous test of a comprehensive 6G virtual twin testbed that includes 50 distributed nodes and five application domains (smart mobility, e-health, industrial IoT, smart cities, and autonomous systems) that the performance is significantly improved: 27.4% increase in threat detection accuracy (reaching 95.0% vs. 76.4% base) can be improved, better privacy preservation with a differential privacy parameter = 0.94 (62% improvement), 21.2% reduction in latency down to 147 ms. The system achieves Precision = 0.968, Recall = 0.959, and F1-score = 0.963 (macro-average), with AUC-ROC = 0.989 across eight attack categories. These results confirm that TwinGuard-Sec is an innovative means of ensuring the safety of cross-domain DT coordination, equipping it with both theoretical frameworks and implementation channels of the next generation intelligent infrastructure systems.

Indexed as

6G networksBlockchainCross-domain securityDigital twinsFederated learningIoT securityPrivacy preservationZero-knowledge proofs

Identifiers

PMID42086711
PMCPMC13333897

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