False data injection (FDI) cyberattacks pose a growing threat to modern power distribution systems in smart cities by manipulating state-estimation processes and provoking covert voltage violations that traditional defense mechanisms fail to detect. Recent industry data indicate that coordinated FDI attacks can distort measurement sets by as little as 3–7%, yet trigger voltage deviations exceeding 10% in vulnerable feeders, resulting in operational instability, unnecessary load curtailments, and elevated outage risk. To address these challenges, this paper proposes a quantum-accelerated digital twin (QDT) framework that integrates quantum optimization algorithms with a high-fidelity digital twin (DT) of the distribution system to detect, localize, and remediate FDI-induced cyberattacks in real time. The rationale behind the approach lies in the superior combinatorial search capability of quantum solvers, which accelerates the identification of falsified measurement vectors and optimal corrective control actions compared with classical methods. In addition, the framework introduces an innovative Bitcoin-mining-oriented virtual energy storage (BMOVES) mechanism that treats mining facilities as dynamically controllable, fast-response electrical loads within smart city demand–response programs. By modulating mining power consumption with sub-second granularity, the proposed BMOVES resource provides up to 18–45% flexible capacity during attack scenarios, enabling voltage restoration without relying on conventional energy storage assets. The unified QDT + BMOVES architecture is validated using the 136-bus Brazilian distribution system, a realistic benchmark for cyber–physical resilience studies. Simulation results demonstrate over 99% FDI detection accuracy, up to an 82% reduction in peak voltage violations, and restoration of operational limits 11 times faster than state-of-the-art classical methods. These findings highlight the transformative potential of integrating quantum computing, digital twins, and nontraditional flexible assets to enhance cyber-resilient power infrastructure in future smart cities.
Ehsan Naderi (2026) studied this question.