Name
Abstract | ||
|---|---|---|
The smart grid systems aim to integrate conventional power grids with modern information communication technology. While intensive research efforts have been focused on ensuring data correctness in AMI data collection and protecting data confidentiality in smart grid communications, less effort has been devoted to privacy protection in smart grid data management and sharing. In smart grid data management, the Advanced Metering Infrastructure (AMI) collects high-frequency energy consumption data, which often contains rich inhabitant and lifestyle information about the end consumers. The data is often shared with various stakeholders, such as the generators, distributors and marketers. However, the utility may not have consent of the users to share potentially sensitive data. In this paper, we develop comprehensive mechanisms to enable privacy-preserving smart data management. First, we analyze the privacy threats and consumer identifiability issues associated with high-frequency AMI data. We then present the first solution based on data sanitization, which eliminates sensitive/identifiable information before sharing usage data with external peers. Meanwhile, we present solutions based on secure multi-party computing to enable external peers to perform aggregate/statistical operations on original metering data in a privacy-preserving manner. Experiments on real-world consumption data demonstrate the validity and effectiveness of the proposed solutions. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/SmartGridComm.2014.7007759 | SmartGridComm |
Keywords | Field | DocType |
information communication technology,consumer identifiability,data confidentiality,energy consumption data,smart grid communications,smart grid systems,privacy-preserving data sharing,ami data collection,power system measurement,smart grid data management,advanced metering infrastructure,power engineering computing,smart power grids,power grids,data sanitization,servers,privacy,smart grids,data privacy | Data collection,Smart grid,Computer security,Data sharing,Server,Computer network,Engineering,Usage data,Information privacy,Energy consumption,Data management | Conference |
ISSN | Citations | PageRank |
2373-6836 | 4 | 0.39 |
References | Authors | |
20 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lei Yang | 1 | 27 | 2.58 |
| Hao Xue | 2 | 4 | 0.39 |
| Fengjun Li | 3 | 233 | 23.55 |