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Innovative Smart Grid Solutions for Fostering Data Security and Effective Privacy Preservation

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Data Analytics for Smart Grids Applications—A Key to Smart City Development

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 247))

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Abstract

Smart grids are crucial for the modernization and optimization of electrical power systems. The generation, distribution, and consumption of electricity are enhanced in terms of monitoring, controlling, and coordination. However, various privacy concerns are present in smart grids, such as identifiable information leakage and appliance usage pattern inference. With the digital transformation of the energy sector, protecting data and preserving privacy is vital for trust and reliability. Secure communication is crucial, requiring network infrastructure security, communication protocols, and intrusion detection and prevention mechanisms. In this work, we present the implementation of techniques like encryption algorithms, key management, and access control models for preserving privacy and enhancing data security in smart grid networks. The methods and techniques presented address secure metering infrastructure, meter data protection, and secure communication. The latest research includes threat detection, firmware and software updates, privacy-preserving data analytics, and blockchain for data security and privacy in smart grids. Robust security measures, privacy-enhancing techniques, and emerging technologies can mitigate risks and ensure data confidentiality, integrity, and availability while preserving privacy and trust. Further, the latest research improvements related to security and privacy in smart grids along with future research directions are discussed.

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Parihar, V., Malik, A., Bhushan, B., Bhattacharya, P., Shankar, A. (2023). Innovative Smart Grid Solutions for Fostering Data Security and Effective Privacy Preservation. In: Kumar Sharma, D., Sharma, R., Jeon, G., Kumar, R. (eds) Data Analytics for Smart Grids Applications—A Key to Smart City Development. Intelligent Systems Reference Library, vol 247. Springer, Cham. https://doi.org/10.1007/978-3-031-46092-0_19

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