Abstract
Aggregating data in the smart grid is an important issue for obtaining the total consumption of a group of households. In order to aggregate data in a privacy preserving manner, it has to be assured that individual contributions are untraceable and only the sum is visible to an aggregator. For billing, network security and statistical analysis data from different types of customers (e.g., industrial, residential) has to be aggregated separately. This paper presents a fault-tolerant and efficient scheme for aggregating data over different groups while preserving the privacy of the households. We propose to build on the Chinese Remainder Theorem for aggregating over groups and on a fault-tolerant and tree-based approach for increasing efficiency. The resulting protocol is evaluated in terms of privacy, complexity and real-world applicability, such as dynamic joins and leaves.
| Original language | English |
|---|---|
| Title of host publication | 2017 IEEE Workshop on Information Forensics and Security, WIFS 2017 |
| Place of Publication | Piscataway, NJ |
| Publisher | IEEE |
| Pages | 1-6 |
| Number of pages | 6 |
| Volume | 2018-January |
| ISBN (Electronic) | 978-1-5090-6769-5 |
| DOIs | |
| Publication status | Published - 2018 |
| Event | WIFS 2017: 9th IEEE International Workshop on Information Forensics and Security - Rennes, France Duration: 4 Dec 2017 → 7 Dec 2017 Conference number: 9 https://project.inria.fr/wifs2017/home/ |
Workshop
| Workshop | WIFS 2017 |
|---|---|
| Country/Territory | France |
| City | Rennes |
| Period | 4/12/17 → 7/12/17 |
| Internet address |
Keywords
- Smart meters
- Protocols
- Cryptography
- Smart grids
- Privacy
- Data privacy
- Fault tolerance
