Visible to the public On the Analysis of Collaborative Anonymity Set Formation (CASF) Method for Privacy in the Smart Grid

TitleOn the Analysis of Collaborative Anonymity Set Formation (CASF) Method for Privacy in the Smart Grid
Publication TypeConference Paper
Year of Publication2017
AuthorsAfrin, S., Mishra, S.
Conference Name2017 IEEE International Symposium on Technologies for Homeland Security (HST)
ISBN Number978-1-5090-6356-7
Keywordsauthentication, CASF method, Collaboration, collaborative anonymity set formation method, consumer privacy, data privacy, distributed anonymization methods, distributed communication, high frequency metering data, human factors, metering data anonymization, NS-3 simulator, power engineering computing, power system security, privacy, privacy preservation, pubcrawl, Public key, Scyther tool, smart grid consumer privacy, Smart Grid Privacy, Smart grids, smart metering data privacy, smart meters, smart power grids
Abstract

The collection of high frequency metering data in the emerging smart grid gives rise to the concern of consumer privacy. Anonymization of metering data is one of the proposed approaches in the literature, which enables transmission of unmasked data while preserving the privacy of the sender. Distributed anonymization methods can reduce the dependency on service providers, thus promising more privacy for the consumers. However, the distributed communication among the end-users introduces overhead and requires methods to prevent external attacks. In this paper, we propose four variants of a distributed anonymization method for smart metering data privacy, referred to as the Collaborative Anonymity Set Formation (CASF) method. The performance overhead analysis and security analysis of the variants are done using NS-3 simulator and the Scyther tool, respectively. It is shown that the proposed scheme enhances the privacy preservation functionality of an existing anonymization scheme, while being robust against external attacks.

URLhttps://ieeexplore.ieee.org/document/7943505
DOI10.1109/THS.2017.7943505
Citation Keyafrin_analysis_2017