智能电网中的安全压缩读取
Secure Compressed Reading in Smart Grids
摘要：
智能电网实时测量能源使用情况，并相应地调整供应和交付，以改善电力传输和分配。为了使电网有效运行，必须以高效和安全的方式将读数从安装的智能电表收集到控制中心。在本文中，我们提出了一个安全的压缩阅读方案来解决这个关键问题。我们观察到，我们收集的真实世界的仪表数据表达了很强的时间相关性，这表明它们在某些领域是稀疏的。我们采用压缩感知技术来利用这种稀疏性，并设计了一个有效的电表数据传输方案。我们的方案实现了压缩感知提供的实质性效率，而不需要事先知道在哪个领域的仪表数据是稀疏的。这与传统的基于压缩感测的方案形成对比，在传统的基于压缩感测的方案中，先验地需要这种稀疏域信息。然后，我们设计了具体的可靠方案，与我们的基于压缩感知的数据传输方案，使我们的抄表可靠和安全。我们提供了性能保证的正确性，效率和安全性，我们提出的方案。通过分析和仿真，我们证明了我们的计划的有效性，并比较其性能与现有技术。
英文摘要：
Smart Grids measure energy usage in real-time and tailor supply and delivery accordingly, in order to improve power transmission and distribution. For the grids to operate effectively, it is critical to collect readings from massively-installed smart meters to control centers in an efficient and secure manner. In this paper, we propose a secure compressed reading scheme to address this critical issue. We observe that our collected real-world meter data express strong temporal correlations, indicating they are sparse in certain domains. We adopt Compressed Sensing technique to exploit this sparsity and design an efficient meter data transmission scheme. Our scheme achieves substantial efficiency offered by compressed sensing, without the need to know beforehand in which domain the meter data are sparse. This is in contrast to traditional compressed-sensing based scheme where such sparse-domain information is required a priori. We then design specific dependable scheme to work with our compressed sensing based data transmission scheme to make our meter reading reliable and secure. We provide performance guarantee for the correctness, efficiency, and security of our proposed scheme. Through analysis and simulations, we demonstrate the effectiveness of our schemes and compare their performance to prior arts.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
