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.
Alnfiai et al. (2026) studied this question.