Private Data Aggregation Enabling Verifiable Multisubset Dynamic Billing in Smart Grids
Efficient power management in smart grids relies on regularly obtaining the electricity usage of each user. However, the aggregation of the electricity usage data may expose user privacy. At present, most existing solutions aggregate the electricity data of the entire user set, which cannot meet the fine-grained requirements of the control center. Therefore, this paper proposes a verifiable privacy-preserving multisubset dynamic billing data aggregation scheme. Firstly, we divide the electricity data into k consecutive subsets and set dynamic pricing rules, such as pricing within a certain range as q<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</inf> and exceeding it as q<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>. Then, the smart meter encrypts the data using the Paillier cryptographic system with the corresponding subset of parameters and uploads them to the aggregation equipment. After the aggregation equipment completes the users’ data aggregation, the ciphertext C is sent to the control center. This process enables the control center to check data integrity and obtain the total number of people, electricity consumption, and costs for different ranges of electricity in a period of time at once, without the need to obtain data for individual users. Analysis and experiments show that this scheme can resist attacks from powerful adversaries on the transmission channel and has practicality and effectiveness.
Authors
- Qian Yang (ORCID: https://orcid.org/0000-0002-2504-5868)
- Dengzhi Liu (ORCID: https://orcid.org/0000-0001-9206-7680)
- Chen Wang (ORCID: https://orcid.org/0000-0002-3951-3159)
- Yi Li (ORCID: https://orcid.org/0000-0003-1720-2760)
- Jian Shen (ORCID: https://orcid.org/0000-0003-0519-9058)
Institutions
- Zhejiang Sci-Tech University (CN)
- Swinburne University of Technology (AU)
Publication Details
- Published
- 2024-12-17
- DOI
- https://doi.org/10.1109/trustcom63139.2024.00164
- Primary Topic
- Internet Traffic Analysis and Secure E-voting
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Zhejiang Sci-Tech University