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.
The prospective arrival of a cryptanalytically relevant quantum computer (CRQC) threatens the asymmetric primitives that protect smart grid communications, protection signalling and identity assertions. Migration to the NIST-standardised post-quantum cryptography (PQC) suite — ML-KEM (FIPS 203) and ML-DSA (FIPS 204) —...
Gulab Kumar Mondal, Dharampal Singh, Arijit Das et al.· JOURNAL OF MECHANICS OF CONT...· 0 citations
The evolution towards 6G networks demands unprecedented levels of automation, security, and quantum resilience to address the complex challenges of autonomous zero-touch networking. Current orchestration frameworks lack comprehensive quantum-resistant security mechanisms and fail to provide adaptive trust management su...
Predictive modelling of brain and critical care conditions requires accuracy, speed, and privacy, yet sensitive clinical data and fragmented healthcare systems hinder AI implementation. Existing Federated Learning frameworks struggle to balance performance, scalability, security, and privacy in real-world medical envir...
S. H., P. C. Renukaradhya, R. R. et al.· Science & Technology Asi...· 0 citations
The advent of quantum computing poses a critical threat to conventional cryptographic systems, potentially rendering many widely used algorithms obsolete. To address this challenge, this study proposes the quantum adaptive security algorithm for key management systems (QASA-KMS), a hybrid security framework that integr...
Neethi Narayanan, S. C. Vigila· International Journal of Adv...· 0 citations
The convergence of quantum computing and the scale of Internet of Things (IoT) deployments creates a compounded security problem: classical public-key cryptography securing today’s IoT traffic is vulnerable to harvest-now, decrypt-later attacks, while the constrained hardware typical of IoT devices limits the security...
Dina Al-Sadi, L. Tawalbeh· IEEE Access· 0 citations
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