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Author

Gyanendra Kumar

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#edge computing Sep 2026

Quantum-Resilient Federated Learning for Real-Time Digital Twin Synchronization in Smart City 6G Networks

Digital Twin (DT) technology, with Federated Learning (FL), enables decentralised and privacyaware intelligence of large-scale infrastructures of smart cities. Quantum computing compromises the existing cryptography systems that underlie existing FL frameworks. The current paper presents a Quantum-Secure FL (QSec-FL) architecture that incorporates both Post-Quantum Cryptography (PQC) and Quantum Key Distribution (QKD) as methods to ensure quantum-resistant communication between the IoT, edge, and cloud layers of 6G networks. The framework facilitates real-time DT synchronisation and ultra-reliable low-latency communication (URLLC) through adaptive model aggregation and secure key management. With the help of a large dataset of SmartCity-6G-QSec, QSec-FL features better robustness, synchronisation integrity, and intrusion resilience than traditional secure FL systems. Additionally, the framework is compliant with the standards of NIST PQC, ETSI QKD, and 3GPP Release 19, ensuring compatibility and readiness for use in future 6G-based infrastructures. QSec-FL is a quantum-resilient security system incorporating federated intelligence to establish a unified, dependable, real-time DT operation and safe AI-based decision-making of the advanced smart cities.

Sasmita Padhy, Naween Kumar, Gyanendra Kumar · 6 citations
Open access 2026

QoE-Driven Multimodal Multi-Agent NDN-Enabled Blockchain Framework for Adaptive 6G Communication Networks

Experimental results demonstrate significant reductions in end-to-end latency, redundant traffic transmission, and synchronization overhead, while improving caching efficiency, traffic utilization, and adaptive content dissemination performance compared with conventional IP-based blockchain communication systems.

A. Yadav, V. Pawar, Abdul Mazid et al. · 1 citation