Re-identification of Smart Meter data

Buchmann, Erik; Böhm, Klemens; Burghardt, Thorben; Keßler, Stephan

doi:10.1007/s00779-012-0513-6

Cited by 44 publications

(17 citation statements)

References 13 publications

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“…It is critical in cases where no personal identifier is assigned to the data. Recent work has shown that there exist many features like the energy consumption between 4 and 8 a.m. or the average wakeup hour that allow precise re-identification [12]. We apply the features described in [12] and compare the achieved accuracy in the original and the transmitted time series.…”

Section: Methodsmentioning

confidence: 98%

“…Recent work has shown that there exist many features like the energy consumption between 4 and 8 a.m. or the average wakeup hour that allow precise re-identification [12]. We apply the features described in [12] and compare the achieved accuracy in the original and the transmitted time series. We expect that methods that modify the original data hinder the correct calculation of these features and therefore complicate re-identification.…”

Section: Methodsmentioning

confidence: 98%

“…Previous work on smart grid data has shown that energy-consumption data allows us to infer activities [2] or private properties [15] of the households, or to re-identify the household owners from the energy consumption [12].…”

Section: Related Workmentioning

confidence: 99%

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Individual privacy constraints on time-series data

Laforet

Buchmann

Böhm

2015

Information Systems

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Section: Methodsmentioning

confidence: 98%

Section: Methodsmentioning

confidence: 98%

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Individual privacy constraints on time-series data

Laforet

Buchmann

Böhm

2015

Information Systems

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“…The study outcome was assessed with respect to energy consumption and delay mainly. Another study towards energy efficiency was put forward by Buchmann et al [38] who have presented an analytical modelling for re-identification of dissipated energy records identical to specific utility feature. The authors have presented an empirical modelling that uses linear and integer linear optimization technique.…”

Section: B Technqiues Towards Energy Efficiencymentioning

confidence: 99%

Research Advancements Towards in Existing Smart Metering over Smart Grid

A¹,

Khan²,

Nagaraj³

2017

ijacsa

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Abstract-The advent of smart meters has automated the entire process of billing generation system over commercial energy usage which was previously done using digital meter. Although western countries practice its usage more, it is still unknown to many developing countries along with its power distribution. Hence, this paper reviews the working principle of smart meters along with the brief of basic operation description. It thoroughly investigates the implementation work towards algorithm design and techniques developed that are being carried out in last five years towards smart meters. The paper examines the various significant technology that has evolved to address the problems in smart meter e.g. performance improvement, energy efficiency, security factor, etc. Finally, a set of research gap is explored after scrutinizing the advantages and limitations of existing techniques followed by brief highlights of the feasible line of research to compensate the unaddressed problems associated with research work direction towards smart meters.

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“…One can conclude personal information [20]. Energy data also allows re-identification of energy consumers [21], even if the data does not contain unique identifiers. Thus, such data must be protected according to data privacy regulations, e.g., Directive 95/46/EC [9] or national legislation [22].…”

Section: Privacy Aspects Of Energy Datamentioning

confidence: 99%

The Costs of Privacy in Local Energy Markets

Buchmann

Keßler

Jochem

et al. 2013

2013 IEEE 15th Conference on Business Informatics

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Many renewable sources for electricity generation are distributed and volatile by nature, and become inefficient and difficult to coordinate with traditional power transmission paths. As a part of the transition from fossil fuel to renewable sources, local energy markets allow an efficient allocation and distribution of energy from local sources to nearby households. When using a discrete time double auction model, bids in such markets reflect the supply and demand of energy. However, since the energy demand of a household contains personal information, such markets are not in line with privacy legislation.In this paper, we investigate the influence of anonymization methods on local energy markets. In particular, we anonymize the bids of the order book, and we compare the CO2 emissions and the expenses of market participants of this allocation with a non-anonymous one. We have modeled the flows of personal data for a local energy auction platform, and we have developed a model for the supply and demand of electricity of a small town in the near future. Our experiments show that with elementary anonymization methods, the impact of anonymization on the costs and on the CO2 emissions is small.

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Re-identification of Smart Meter data

Cited by 44 publications

References 13 publications

Individual privacy constraints on time-series data

Individual privacy constraints on time-series data

Research Advancements Towards in Existing Smart Metering over Smart Grid

The Costs of Privacy in Local Energy Markets

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