Private memoirs of a smart meter

Molina–Markham, Andrés; Shenoy, Prashant; Fu, Kevin; Cecchet, Emmanuel; Irwin, David

doi:10.1145/1878431.1878446

Cited by 428 publications

(258 citation statements)

References 11 publications

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“…The system allows users to observe their own power consumption down to the minute which opens up the possibility of optimizing their usage patterns to lower overall power consumption [11]. In addition to this, the smart meter system provides users with a platform for home automation which can further lower their power consumption by automatically turning off unused devices or starting devices based on electricity prices [3].…”

Section: Smart Meter Privacy Concerns and Access Rightsmentioning

confidence: 99%

“…In addition to this, the smart meter system provides users with a platform for home automation which can further lower their power consumption by automatically turning off unused devices or starting devices based on electricity prices [3]. However, the possibility of reading fine-grained power consumption data also posses several privacy issues due to the possibility of deriving personal behavior patterns from the power consumption data, for example it is possible to figure out if a person is home during their sick leave or if they left late for work by observing when they consume power [11]. As such it would be favorable to regulate whom that has access to this data and in how fine a granularity the data can be extracted in relation to the entity that wants to observe the data.…”

Section: Smart Meter Privacy Concerns and Access Rightsmentioning

confidence: 99%

“…There are many security and privacy aspects to take into account when designing and implementing a smart meter system: a major privacy concern, which is also the main focus of this paper, is that power companies can build highly detailed power consumption profiles for individual homes. To prevent this, power companies are only allowed to access the measured power consumption at certain time intervals [11]. For further smart meter security issues, see [3,2].…”

Section: Introductionmentioning

confidence: 99%

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The Timed Decentralised Label Model

et al. 2015

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Section: Smart Meter Privacy Concerns and Access Rightsmentioning

confidence: 99%

Section: Smart Meter Privacy Concerns and Access Rightsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Timed Decentralised Label Model

et al. 2015

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“…Molina-Markham et al [5] propose a zero-knowledge protocol allowing the smart meters to calculate both the aggregate consumption and the energy bill of each household without releasing fine-grained information to the utility companies. The protocol is computationally quite expensive and requires a potentially very large number of Neighborhood Gateways.…”

Section: Related Workmentioning

confidence: 99%

A security framework for smart metering with multiple data consumers

Rottondi

Verticale

Capone

2012

2012 Proceedings IEEE INFOCOM Workshops

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Abstract-The increasing diffusion of Automatic Meter Reading (AMR) has raised many concerns about the protection of personal data related to energy, water or gas consumption, from which details about the habits of the users can be inferred. On the other hand, aggregated measurements about consumption are crucial for several goals, including resource provisioning, forecasting, and monitoring. This paper proposes a framework for allowing information Consumers, such as utilities and third parties, to collect data with different levels of spatial and temporal aggregation from smart meters without revealing information about individual customers.The proposed infrastructure introduces a new set of functional nodes, namely the Privacy Preserving Nodes (PPNs), which collect customer data masked by means of a secret sharing scheme with homomorphic properties, and aggregate them directly in the masked domain, according to the Consumer's needs and access rights. The information Consumers can recover the aggregated data by collecting multiple shares from the PPNs.The paper describes an Integer Linear Programming formulation and a greedy algorithm to address the problem of deploying the information flows between the information Producers (i.e. the customers), the PPNs, and the Consumers and evaluates the scalability of the infrastructure both under the assumption that the communication network is reliable and timely and in presence of communication errors.

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“…To surface privacy concerns, Molina-Markham et al recently highlighted that monitoring the home's aggregate power consumption can reveal private information about a homeowner's activity [21]. This work used methods from prior work in the energy monitoring and ubiquitous computing communities.…”

Section: Related Workmentioning

confidence: 99%

Televisions, video privacy, and powerline electromagnetic interference

Enev

Gupta

Kohno

et al. 2011

Proceedings of the 18th ACM Conference on Computer and Communications Security

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We conduct an extensive study of information leakage over the powerline infrastructure from eight televisions (TVs) spanning multiple makes, models, and underlying technologies. In addition to being of scientific interest, our findings contribute to the overall debate of whether or not measurements of residential powerlines reveal significant information about the activities within a home. We find that the power supplies of modern TVs produce discernible electromagnetic interference (EMI) signatures that are indicative of the video content being displayed. We measure the stability of these signatures over time and across multiple instances of the same TV model, as well as the robustness of these signatures in the presence of other noisy electronic devices connected to the same powerline.

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Private memoirs of a smart meter

Cited by 428 publications

References 11 publications

The Timed Decentralised Label Model

The Timed Decentralised Label Model

A security framework for smart metering with multiple data consumers

Televisions, video privacy, and powerline electromagnetic interference

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