SunSpot: Exposing the Location of Anonymous Solar-powered Homes
SunSpot: Exposing the Location of Anonymous Solar-powered Homes
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SunSpot：曝光匿名太阳能房屋的位置
DOI：
10.1145/2993422.2993573
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Prashant J. Shenoy
中科院分区：
文献类型：
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作者：
Dong Chen;Srinivasan Iyengar;David E. Irwin;Prashant J. Shenoy
由于太阳能组件价格的快速下降，越来越多的房主正在部署并网太阳能系统。这些太阳能家庭产生的能量由公用事业公司和第三方使用联网电能表进行监测，这些电能表以精细的间隔记录和传输能源数据。如果这种能量数据不与标识帐户信息(例如，名称和地址)相关联，则认为它是匿名的。因此，来自这些“匿名”家庭的能源数据往往没有得到安全的处理：它们通常以明文形式在互联网上传输，未加密地存储在云中，与第三方能源分析公司共享，甚至通过互联网公开可用。大量的前期工作表明，能源消耗数据容易受到多种攻击，这些攻击会对其进行分析，以揭示一系列关于居住者活动的敏感私人信息。然而，如果不知道房子的位置，这些攻击是没有用的。我们的关键见解是，太阳能数据不是匿名的：因为地球上的每个位置都有唯一的太阳签名，所以它嵌入了详细的位置信息。为了探索这种隐私威胁的严重性和程度，我们设计太阳黑子使用太阳能数据来定位“匿名”的太阳能供电房屋。我们根据14个安装了屋顶太阳能的家庭的公开能源数据来评估太阳黑子。我们发现，太阳黑子能够将太阳能家庭定位到一个小的感兴趣区域，该区域位于给定能量数据分辨率的最小可能区域附近，例如，对于每秒分辨率和每分钟分辨率，分别在~500米和~28公里半径内。太阳黑子然后使用卫星数据的众包图像处理来识别该区域内的太阳能房屋，然后应用额外的过滤器来识别特定的房屋。
Homeowners are increasingly deploying grid-tied solar systems due to the rapid decline in solar module prices. The energy produced by these solar-powered homes is monitored by utilities and third parties using networked energy meters, which record and transmit energy data at fine-grained intervals. Such energy data is considered anonymous if it is not associated with identifying account information, e.g., a name and address. Thus, energy data from these "anonymous" homes is often not handled securely: it is routinely transmitted over the Internet in plaintext, stored unencrypted in the cloud, shared with third-party energy analytics companies, and even made publicly available over the Internet. Extensive prior work has shown that energy consumption data is vulnerable to multiple attacks, which analyze it to reveal a range of sensitive private information about occupant activities. However, these attacks are useless without knowledge of a home's location. Our key insight is that solar energy data is not anonymous: since every location on Earth has a unique solar signature, it embeds detailed location information. To explore the severity and extent of this privacy threat, we design SunSpot to localize "anonymous" solar-powered homes using their solar energy data. We evaluate SunSpot on publicly-available energy data from 14 homes with rooftop solar. We find that SunSpot is able to localize a solar-powered home to a small region of interest that is near the smallest possible area given the energy data resolution, e.g., within a ~500m and ~28km radius for per-second and per-minute resolution, respectively. SunSpot then identifies solar-powered homes within this region using crowd-sourced image processing of satellite data before applying additional filters to identify a specific home.