Anonymous yet Verifiable Privacy-Preserving Demand Response
- ,
- Emad Heydari Beni,
- Daniele Marletta,
- Maryam Sheikhi Garjan
- ,
- ,
- ,
- KU Leuven,
- University of Catania
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewPublication Information
Output type
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewOriginal language
EnglishPages from-to (Number of pages)
Pages 62-82 (21 pages)Publication milestones
- Published - 21/07/2026
Publication status
Published - 21/07/2026
Publisher
Springer, United States, GermanyBook series
- Book series name: Lecture Notes in Computer Science
ISSN: 0302-9743
ISBN (Print)
9783032332592ISBN (Electronic)
978-3-032-33260-8Publication IDs
- ORCID: /0000-0002-2917-9601/work/221248770
Host publication title
Data and Applications Security and Privacy XLAbstract
Demand Response (DR) in energy systems is a flexibility mechanism enabling consumers to modify their electricity demand in response to signals from network operators, designed to ensure power grid reliability. In particular, incentive-based DR programs, in which consumers provide load reduction in exchange for financial remuneration, have proven more effective than alternative approaches such as price-based programs. However, incentive-based approaches have taken only partial account of privacy considerations, mainly because they require smart meters to disclose users’ energy baselines and consumption patterns to aggregators in order to determine rewards. In this paper, we propose a privacy-preserving scheme that supports incentive-based DR programs while ensuring the confidentiality of user data and identities. We prove that our scheme provides data privacy, participation privacy, and public verifiability, and we present a prototype implementation together with a performance evaluation. Our results show that our construction is practical for real-world DR deployments with considerably large user populations.
