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Smart Meter Privacy for Multiple Users in the Presence of an Alternative Energy Source

机译:存在替代能源的情况下,多个用户的智能电表隐私

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Smart meters (SMs) measure and report users’ energy consumption to the utility provider (UP) in almost real-time, providing a much more detailed depiction of the consumer’s energy consumption compared to their analog counterparts. This increased rate of information flow to the UP, together with its many potential benefits, raise important concerns regarding user privacy. This paper investigates, from an information theoretic perspective, the privacy that can be achieved in a multiuser SM system in the presence of an alternative energy source (AES). To measure privacy, we use the mutual information rate between the users’ real energy consumption profile and SM readings that are available to the UP. The objective is to characterize the privacy-power function, defined as the minimal information leakage rate that can be obtained with an average power-limited AES. We characterize the privacy-power function in a single letter form when the users’ energy demands are assumed to be independent and identically distributed over time. Moreover, for binary and exponentially distributed energy demands, we provide an explicit characterization of the privacy-power function. For any discrete energy demands, we demonstrate that the privacy-power function can always be efficiently evaluated numerically. Finally, for continuous energy demands, we derive an explicit lower bound on the privacy-power function, which is tight for exponentially distributed loads.
机译:智能电表(SM)几乎实时地测量用户的能耗并将其报告给公用事业提供商(UP),与模拟用户相比,它能更详细地描述消费者的能耗。信息流到UP的速率增加,以及其许多潜在的好处,引起了有关用户隐私的重要问题。本文从信息理论的角度研究了在存在替代能源(AES)的情况下在多用户SM系统中可以实现的隐私。为了衡量隐私,我们使用用户的实际能耗状况与UP可用的SM读数之间的相互信息率。目的是表征隐私权函数,将其定义为平均功率受限AES可获得的最小信息泄漏率。当假设用户的能量需求独立且随时间分布均匀时,我们以单个字母形式描述隐私权功能。此外,对于二进制和指数分布的能源需求,我们提供了隐私权函数的显式表征。对于任何离散的能量需求,我们证明了隐私权函数始终可以通过数字有效地评估。最后,对于连续的能源需求,我们得出了隐私权函数的一个明确的下界,对于指数分布的负载来说,这个下界是紧密的。

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