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Erschienen in: Optical and Quantum Electronics 6/2024

01.06.2024

Incorporating quantum key distribution and reinforcement learning for secure and efficient smart grid advanced metering infrastructure

verfasst von: G. Starlin Beula, S. Wilfred Franklin

Erschienen in: Optical and Quantum Electronics | Ausgabe 6/2024

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Abstract

The Smart Grid AMI is at the forefront of modernizing energy management for efficient energy distribution and maintaining grid reliability. However, the seamless flow of data within AMI introduces critical security challenges, necessitating innovative approaches to ensure secure data transmission. This paper addresses these challenges by proposing a Quantum Key Distribution (QKD) based on Multi-Objective Optimization (MOO) and Reinforcement Learning (RL) framework for secure data transmission within the Smart Grid AMI. Primarily, we formulate the routing problem as a MOO challenge with four primary objectives namely, energy efficiency, latency minimization, reliability, and security to capture the essence of efficient and secure data transmission. Further, we introduce an RL agent based on the Proximal Policy Optimization (PPO) algorithm for robust policy learning. The RL agent by exploring diverse routing actions and receiving rewards optimizes the routing decisions within the network environment based on the objectives specified in the multi-objective function (MOF). A novel MOF quantifies trade-offs between security and performance metrics, integrating QKD-based security metrics with traditional optimization objectives. This function guides the RL agent in making informed routing decisions. Through extensive simulations using the NS-2 simulator in a realistic Smart Grid AMI environment, the proposed approach obtained energy consumption of 750 J, latency of 55 ms, and security level of 96% and also revealed significant improvements compared to conventional techniques widely employed for secured communication in AMI networks. Overall, the simulation results exhibited that the proposed method showed outstanding performance by achieving energy efficiency of 0.95, latency reduction of 0.92, reliability improvement of 0.94, and security enhancement of 0.96. Overall, this integration offers a pioneering solution to address the evolving security challenges in the Smart Grid landscape and contributes to the advancement of secure data transmission in Smart Grid AMI networks, fostering a resilient and secure energy ecosystem.

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Metadaten
Titel
Incorporating quantum key distribution and reinforcement learning for secure and efficient smart grid advanced metering infrastructure
verfasst von
G. Starlin Beula
S. Wilfred Franklin
Publikationsdatum
01.06.2024
Verlag
Springer US
Erschienen in
Optical and Quantum Electronics / Ausgabe 6/2024
Print ISSN: 0306-8919
Elektronische ISSN: 1572-817X
DOI
https://doi.org/10.1007/s11082-024-06600-7

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