热和隐私的结合:防止智能电表的占用检测

Dong Chen, David E. Irwin, P. Shenoy, Jeannie R. Albrecht
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引用次数: 38

摘要

电力公司正在迅速部署能够实时记录和传输用电量的智能电表。先前的研究表明,智能电表数据间接泄露了家庭活动的敏感信息,这些信息可能很有价值。智能电表显示的敏感信息的一个重要例子是占用情况——是否有人在家以及何时在家。正如之前的工作也表明的那样,占用率非常容易检测,因为它与简单的统计指标高度相关,例如功率的平均值、方差和范围。不幸的是,先前的研究使用化学能量存储,例如电池,来防止电器功率特征检测,当应用于占用检测时,成本过高。为了解决这个问题,我们建议使用许多家庭中已经存在的大型弹性热负荷(如电热水器和空间加热器)的热能储存来防止占用检测。从本质上讲,我们的方法,我们称之为热和隐私结合(CHPr),控制这些大负载的用电量,使它看起来像有人一直在家。我们设计了一个具有chpr功能的热水器,它可以调节其能源使用,以掩盖占用而不违反其目标,例如,按需提供热水,并在模拟和使用原型中对其进行评估。我们的研究结果表明,在一个有代表性的家庭中,一个启用了50加仑chpr的热水器将基于阈值的占用检测攻击的马修斯相关系数(二元分类器性能的标准度量)降低了10倍(从0.44降至0.045),有效地防止了占用检测,而不需要额外的成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combined heat and privacy: Preventing occupancy detection from smart meters
Electric utilities are rapidly deploying smart meters that record and transmit electricity usage in real-time. As prior research shows, smart meter data indirectly leaks sensitive, and potentially valuable, information about a home's activities. An important example of the sensitive information smart meters reveal is occupancy-whether or not someone is home and when. As prior work also shows, occupancy is surprisingly easy to detect, since it highly correlates with simple statistical metrics, such as power's mean, variance, and range. Unfortunately, prior research that uses chemical energy storage, e.g., batteries, to prevent appliance power signature detection is prohibitively expensive when applied to occupancy detection. To address this problem, we propose preventing occupancy detection using the thermal energy storage of large elastic heating loads already present in many homes, such as electric water and space heaters. In essence, our approach, which we call Combined Heat and Privacy (CHPr), controls the power usage of these large loads to make it look like someone is always home. We design a CHPr-enabled water heater that regulates its energy usage to mask occupancy without violating its objective, e.g., to provide hot water on demand, and evaluate it in simulation and using a prototype. Our results show that a 50-gallon CHPr-enabled water heater decreases the Matthews Correlation Coefficient (a standard measure of a binary classifier's performance) of a threshold-based occupancy detection attack in a representative home by 10x (from 0.44 to 0.045), effectively preventing occupancy detection at no extra cost.
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