Smart Grid Privacy via Anonymization of Smart Metering Data
By Costas Efthymiou, Georgios Kalogridis. 2010 First IEEE International Conference on Smart Grid Communications, 2010
688 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Control and Systems Engineering, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/d2bad15cf4e148c1c0ec9b92f46d5b769104495f
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Citations in the corpus
- Privacy-preserving smart metering (2011, background): “The NIST privacy subgroup [37] suggests anonymizing traces of readings, as proposed by Efthymiou et al. [16], but also warns of the ease of reidentification .”
- Cloud Computing Applications for Smart Grid: A Survey (2015, background): “ers proposed various security and privacy schemes to motivate the customers [12], [67], [69], [70], [100], [101], [102], [103], [107].”
- The role of communication systems in smart grids: Architectures, technical solutions and research challenges (2013, background): “In [317] this is achieved by assuming that a trusted third party provides pseudonymous identities, which are then used to anonymize high-frequency metering data.”
- Two Is Not Enough: Privacy Assessment of Aggregation Schemes in Smart Metering (2017, background): “The use of trusted third parties has been proposed in [17] and [18] in order to anonymize consumption data.”
- Cyber Security and Privacy Issues in Smart Grids (2012, background): “[45] proposed an escrow-based anonymization scheme to prevent personal information from being tracked by unauthorized third parties.”
- Role-Dependent Privacy Preservation for Secure V2G Networks in the Smart Grid (2014, background): “Additionally, several works have studied the general security issues in the smart grid, including security frameworks [13]–[19], authentication protocols [20]–[23], encryption and key management [24], [25], and privacy-preserving protocols [26], [27].”
- Privacy-Preserving and Efficient Aggregation Based on Blockchain for Power Grid Communications in Smart Communities (2018, methodology): “Anonymization [3] [4] is a common technique to protect user’s identity.”
- Private memoirs of a smart meter (2010, background): “For example, it would be possible to use mixnets or other ways to communicate power tuples from the smart meters to the gateways, see for example [6] .”
- Smart Grid — The New and Improved Power Grid: A Survey (2012, positive): “Kalogridis et al. [121] introduced a load signature moderation system that protects smart metering data privacy.”
- Smart Grid Communications: Overview of Research Challenges, Solutions, and Standardization Activities (2011, methodology): “An example of this direction is studied in [63] where a secure escrow protocol is proposed to securely anonymize the ID of frequent metering data sent by a smart meter.”
- DP-ADMM: ADMM-Based Distributed Learning With Differential Privacy (2018, background): “d variants of ADMM. Data privacy. There have been tremendous research efforts on data privacy guarantee. An intuitive approach is anonymity, which protects user privacy by hiding their identity [18], [19]. However, when multiple data sources are linked together, it is easy to recover the hidden user”
- Security and Privacy in Decentralized Energy Trading Through Multi-Signatures, Blockchain and Anonymous Messaging Streams (2018, background): “Efthymiou and Kalogridis [26] discuss a secure mechanism which allows to anonymize readings sent by a smart meter.”
- Aggregated-Proofs Based Privacy-Preserving Authentication for V2G Networks in the Smart Grid (2012, background): “…home local aggregator , and home virtual battery vehicle of the same group, and the home mode is launched by ; out-group entities to include the visiting battery vehicles s, visiting local aggregator , and visiting virtual battery vehicle of different groups, and the visiting mode is launched by .”
- Preserving data integrity for smart grid data aggregation (2012, methodology): “proposed an anonymization based approach to hide the identity of smart meters in high-frequency metering data using pseudonyms [12].”