Name
Abstract | ||
|---|---|---|
Data aggregation has been widely researched to address the privacy concern when data is published, meanwhile, data aggregation only obtains the sum or average in an area. In reality, more fine-grained data brings more value for data consumers, such as more accurate management, dynamic price-adjusting in the grid system, etc. In this paper, a multi-subset data aggregation scheme for the smart grid is proposed without a trusted third party, in which the control center collects the number of users in different subsets, and obtains the sum of electricity consumption in each subset, meantime individual user's data privacy is still preserved. In addition, the dynamic and flexible user management mechanism is guaranteed with the secret key negotiation process among users. The analysis shows MSDA not only protects users' privacy to resist various attacks but also achieves more functionality such as multi-subset aggregation, no reliance on any trusted third party, dynamicity. And performance evaluation demonstrates that MSDA is efficient and practical in terms of communication and computation overhead. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1007/s11704-021-0316-x | FRONTIERS OF COMPUTER SCIENCE |
Keywords | DocType | Volume |
multi-subset data aggregation, privacy-preserving, smart gird, dynamic user management | Journal | 16 |
Issue | ISSN | Citations |
1 | 2095-2228 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhixin Zeng | 1 | 2 | 1.05 |
| Xiaodi Wang | 2 | 0 | 0.34 |
| Yining Liu | 3 | 3 | 1.38 |
| Liang Chang | 4 | 118 | 34.68 |