Smart Meter Privacy for Multiple Users in the Presence of an Alternative Energy Source
Smart Meter Privacy for Multiple Users in the Presence of an Alternative Energy Source
复制标题
在存在替代能源的情况下，多个用户的智能电表隐私
DOI：
10.1109/tifs.2014.2365365
复制
发表时间：
2013
影响因子：
6.8
通讯作者：
Deniz Gündüz
中科院分区：
文献类型：
--
作者：
J. Gómez;Deniz Gündüz
智能电表（SM）几乎实时地测量并向公用事业提供商（UP）报告用户的能源消耗，与模拟电表相比，能够更详细地描述消费者的能源消耗。这种信息流到UP的速度的增加，连同其许多潜在的好处，引起了关于用户隐私的重要关注。本文从信息论的角度研究了在多用户SM系统中存在替代能源（AES）的情况下可以实现的隐私。为了衡量隐私，我们使用用户的真实的能源消耗概况和UP可用的SM读数之间的互信息率。我们的目标是表征的隐私功率函数，定义为最小的信息泄漏率，可以得到一个平均功率限制的AES。当用户的能量需求被假设为独立同分布时，我们以单个字母的形式描述了隐私-功率函数。此外，对于二进制和指数分布的能源需求，我们提供了一个明确的特征的隐私功率函数。对于任何离散的能源需求，我们证明了隐私权函数总是可以有效地进行数值计算。最后，对于连续的能源需求，我们推导出一个显式的下界的隐私功率函数，这是紧指数分布的负载。
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.