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Smart and Practical Privacy-Preserving Data Aggregation for Fog-Based Smart Grids
IEEE Transactions on Information Forensics and Security ( IF 6.3 ) Pub Date : 8-5-2020 , DOI: 10.1109/tifs.2020.3014487
Shuai Zhao , Fenghua Li , Hongwei Li , Rongxing Lu , Siqi Ren , Haiyong Bao , Jian-Hong Lin , Song Han

With the increasingly powerful and extensive deployment of edge devices, edge/fog computing enables customers to manage and analyze data locally, and extends computing power and data analysis applications to network edges. Meanwhile, as the next generation of the power grid, the smart grid can achieve the goal of efficiency, economy, security, reliability, use safety and environmental friendliness for the power grid. However, privacy and secure issues in fog-based smart grid communications are challenging. Without proper protection, customers’ privacy will be readily violated. This article presents a smart and practical Privacy-preserving Data Aggregation (PDA) scheme with smart pricing and packing method for fog-based smart grids, which achieves diversified tariffs, multifunctional statistics and efficiency. Especially, we first propose a smart PDA scheme with Smart Pricing (PDA-SP). With PDA-SP, the Control Center (CC) can compute more complex and higher-order aggregation statistics to provide various services, provide diversiform pricing strategies and choose a double-winning strategy. Subsequently, we put forward a practical PDA scheme with Packing Method (PDA-PM), which is able to reduce the size of encrypted data and improve performance in performing various secure computations. Moreover, we extend our original packing method and present a more useful packing method, which can handle general vectors with large entries. The security analysis shows that our proposed scheme is secure against many threats. The performance evaluation reveals that the computation and communication overheads of our proposed scheme are effectively reduced by employing the Somewhat Homomorphic Encryption (SHE), and our packing method can further significantly reduce these overheads.

中文翻译:


基于雾的智能电网的智能实用的隐私保护数据聚合



随着边缘设备的日益强大和广泛部署,边缘/雾计算使客户能够在本地管理和分析数据,并将计算能力和数据分析应用扩展到网络边缘。同时,智能电网作为下一代电网,可以实现电网高效、经济、安全、可靠、使用安全、环境友好的目标。然而,基于雾的智能电网通信中的隐私和安全问题具有挑战性。如果没有适当的保护,客户的隐私很容易受到侵犯。本文提出了一种智能实用的基于雾的智能电网的具有智能定价和打包方法的隐私保护数据聚合(PDA)方案,实现了资费多元化、统计多功能和效率提高。特别是,我们首先提出了一种具有智能定价的智能PDA方案(PDA-SP)。通过PDA-SP,控制中心(CC)可以计算更复杂、更高阶的聚合统计来提供各种服务,提供多样化的定价策略并选择双赢策略。随后,我们提出了一种实用的带打包方法的PDA方案(PDA-PM),它能够减少加密数据的大小并提高执行各种安全计算的性能。此外,我们扩展了原始的打包方法,并提出了一种更有用的打包方法,它可以处理具有大条目的通用向量。安全分析表明,我们提出的方案可以抵御许多威胁。性能评估表明,通过采用同态加密(SHE),我们提出的方案的计算和通信开销得到了有效降低,并且我们的打包方法可以进一步显着降低这些开销。
更新日期:2024-08-22
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