F-DETA: A Framework for Detecting Electricity Theft Attacks in Smart Grids
F-DETA: A Framework for Detecting Electricity Theft Attacks in Smart Grids
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F-DETA：智能电网窃电攻击检测框架
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
W. Sanders
中科院分区：
文献类型：
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作者：
V. Krishna;Kiryung Lee;G. Weaver;R. Iyer;W. Sanders
窃电是世界各地公用事业公司的一个主要关注点，每年导致数十亿美元的损失。尽管提高用户智能电表与公用事业公司之间的通信能力能够实现许多智能电网功能，但这些通信可能会遭到破坏，从而使攻击者能够窃电。此类攻击最近已开始出现，因此切实且迫切需要一个框架来防范它们。在本文中，我们做出了三项主要贡献。首先，据我们所知，我们在文献中对窃电攻击进行了最全面的分类。这些攻击是根据它们是否能够规避行业当前使用的安全措施以及在不同的电价方案下是否可能发生来分类的。其次，我们提出了一种基于库尔贝克 - 莱布勒（KL）散度的窃电检测方法，以检测巧妙设计的、能够规避相关工作中提出的检测方法的窃电攻击。最后，我们使用基于真实智能电表数据的虚假数据注入来评估我们的检测方法。对于不同的攻击类别，我们表明与先前工作中的检测方法相比，我们的检测方法极大地减少了窃电情况。
Electricity theft is a major concern for utilities all over the world, and leads to billions of dollars in losses every year. Although improving the communication capabilities between consumer smart meters and utilities can enable many smart grid features, these communications can be compromised in ways that allow an attacker to steal electricity. Such attacks have recently begun to occur, so there is a real and urgent need for a framework to defend against them. In this paper, we make three major contributions. First, we develop what is, to our knowledge, the most comprehensive classification of electricity theft attacks in the literature. These attacks are classified based on whether they can circumvent security measures currently used in industry, and whether they are possible under different electricity pricing schemes. Second, we propose a theft detector based on Kullback-Leibler (KL) divergence to detect cleverly-crafted electricity theft attacks that circumvent detectors proposed in related work. Finally, we evaluate our detector using false data injections based on real smart meter data. For the different attack classes, we show that our detector dramatically mitigates electricity theft in comparison to detectors in prior work.