PMDA: Privacy-Preserving Multi-Functional Data Aggregation Without TTP in Smart Grid
Title | PMDA: Privacy-Preserving Multi-Functional Data Aggregation Without TTP in Smart Grid |
Publication Type | Conference Paper |
Year of Publication | 2018 |
Authors | He, Z., Pan, S., Lin, D. |
Conference Name | 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE) |
Date Published | aug |
ISBN Number | 978-1-5386-4388-4 |
Keywords | composability, cryptography, data aggregation, data privacy, electricity readings, Energy management, Human Behavior, Meters, Metrics, Multi-functional computation, multifunctional aggregation, PMDA, power engineering computing, privacy, privacy flaws, privacy leakage, privacy preserving, privacy protection, privacy-preserving aggregation, privacy-preserving multifunctional data aggregation, pubcrawl, security, security analysis, Smart grid, Smart Grid Privacy, Smart grids, smart meters, smart power grids, trusted third party, TTP |
Abstract | In the smart grid, residents' electricity usage needs to be periodically measured and reported for the purpose of better energy management. At the same time, real-time collection of residents' electricity consumption may unfavorably incur privacy leakage, which has motivated the research on privacy-preserving aggregation of electricity readings. Most previous studies either rely on a trusted third party (TTP) or suffer from expensive computation. In this paper, we first reveal the privacy flaws of a very recent scheme pursing privacy preservation without relying on the TTP. By presenting concrete attacks, we show that this scheme has failed to meet the design goals. Then, for better privacy protection, we construct a new scheme called PMDA, which utilizes Shamir's secret sharing to allow smart meters to negotiate aggregation parameters in the absence of a TTP. Using only lightweight cryptography, PMDA efficiently supports multi-functional aggregation of the electricity readings, and simultaneously preserves residents' privacy. Theoretical analysis is provided with regard to PMDA's security and efficiency. Moreover, experimental data obtained from a prototype indicates that our proposal is efficient and feasible for practical deployment. |
URL | https://ieeexplore.ieee.org/document/8456023 |
DOI | 10.1109/TrustCom/BigDataSE.2018.00154 |
Citation Key | he_pmda:_2018 |
- privacy leakage
- TTP
- trusted third party
- smart power grids
- smart meters
- Smart Grids
- Smart Grid Privacy
- Smart Grid
- Security analysis
- security
- pubcrawl
- privacy-preserving multifunctional data aggregation
- privacy-preserving aggregation
- privacy protection
- privacy preserving
- composability
- privacy flaws
- privacy
- power engineering computing
- PMDA
- multifunctional aggregation
- Multi-functional computation
- Metrics
- Meters
- Human behavior
- energy management
- electricity readings
- data privacy
- data aggregation
- Cryptography