Privacy for Smart Meters: Towards Undetectable Appliance Load Signatures

By Georgios Kalogridis, Costas Efthymiou, Stojan Z. Denic, Tim A. Lewis, Rafael Cepeda. 2010 First IEEE International Conference on Smart Grid Communications, 2010

462 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/3283c400c07487b1a2156ac448dedc447e6d9a50

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Citations in the corpus

Computational Needs for the Next Generation Electric Grid (2011, background): “This work includes disjunctive cutting planes [71], Gomory cuts [16] and perspective cuts and reformulations [35, 39].”
Critical infrastructure protection: Requirements and challenges for the 21st century (2015, background): “Kalogridis et al. proposed in [52] a power management model based on the use of batteries in appliances in order to register different load signatures inside the smart meter thereby hiding real electricity usage values.”
Technical Privacy Metrics (2015, methodology): “uch variability in data is accounted for by a model for the data. In smart metering, the model is a linear regression tted to obfuscated load transitions dp(t), resulting in predicted values dp^ (t) [Kalogridis et al. 2010]. The coecient of determination compares the error sum of squares SS E and th”
A Survey on Cyber Security for Smart Grid Communications (2012, background): “In [59], the authors presented a home electrical power routing scheme that can be used to moderate the home’s load signature in order to hide appliance usage information.”
Cyber Security and Privacy Issues in Smart Grids (2012, background): “[44] designed a system that utilized a power router and a rechargeable battery to hide or obscure load signatures in a home area.”
Smart Grid — The New and Improved Power Grid: A Survey (2012, unknown): “[121] introduced a load signature moderation system that protects smart metering data privacy.”
The role of communication systems in smart grids: Architectures, technical solutions and research challenges (2013, background): “Finally, an alternative approach is proposed in [321,322] by assuming that smart homes will contain a variety of energy storage and generation systems, which can be used to obfuscate appliance load signatures by randomly mixing utility electricity with electricity from local generators.”
Two Is Not Enough: Privacy Assessment of Aggregation Schemes in Smart Metering (2017, background): “[19] propose to blur the load signature of individual smart meters – that is the unique patterns of every load profile, in order to achieve privacy, while Chim et al.”
Private memoirs of a smart meter (2010, background): “An alternative approach to protect privacy is adding noise to load signatures using rechargeable batteries [8].”
Smart meter privacy using a rechargeable battery: Minimizing the rate of information leakage (2011, methodology): “This special case is, thus, the best-effort algorithm of [8] for our binary-load binary-battery model.”
I Have a DREAM! (DiffeRentially privatE smArt Metering) (2011, background): “Several papers addressed the privacy problems of smart meters in the recent past [9, 19, 1, 2, 3, 21, 15, 12].”