Blockchain and Demand Response: Zero-Knowledge Proofs for Energy Transactions Privacy.

blockchain demand response energy data privacy energy flexibility zero-knowledge proof

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
05 Oct 2020
Historique:
received: 15 09 2020
revised: 30 09 2020
accepted: 01 10 2020
entrez: 8 10 2020
pubmed: 9 10 2020
medline: 9 10 2020
Statut: epublish

Résumé

Nowadays, the adoption of demand response programs is still lagging due to the prosumers' lack of awareness, fear of losing control and privacy of energy data, etc. Programs decentralization, by adopting promising technologies such as blockchain, may bring significant advantages in terms of transparency, openness, improved control, and increased active participation of prosumers. Nevertheless, even though in general the transparency of the public blockchain is a desirable feature in the energy domain, the prosumer energy data is sensitive and rather private, thus, a privacy-preserving solution is required. In this paper, we present a decentralized implementation of demand response programs on top of the public blockchain which deals with the privacy of the prosumer's energy data using zero-knowledge proofs and validates on the blockchain the prosumer's activity inside the program using smart contracts. Prosumer energy data is kept private, while on the blockchain it is stored a zero-knowledge proof that is generated by the prosumer itself allowing the implementation of functions to validate potential deviations from the request and settle prosumer's activity. The solution evaluation results are promising in terms of ensuring the privacy of prosumer energy data stored in the public blockchain and detecting potential data inconsistencies.

Identifiants

pubmed: 33027996
pii: s20195678
doi: 10.3390/s20195678
pmc: PMC7583903
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Horizon 2020 Framework Programme
ID : 774478

Références

Sensors (Basel). 2018 Jan 09;18(1):
pubmed: 29315250
Sensors (Basel). 2019 Jul 10;19(14):
pubmed: 31295826
Sensors (Basel). 2019 Nov 08;19(22):
pubmed: 31717262
Sensors (Basel). 2020 Apr 27;20(9):
pubmed: 32349402

Auteurs

Claudia Daniela Pop (CD)

Computer Science Department, Technical University of Cluj-Napoca, Memorandumului 28, 400114 Cluj-Napoca, Romania.

Marcel Antal (M)

Computer Science Department, Technical University of Cluj-Napoca, Memorandumului 28, 400114 Cluj-Napoca, Romania.

Tudor Cioara (T)

Computer Science Department, Technical University of Cluj-Napoca, Memorandumului 28, 400114 Cluj-Napoca, Romania.

Ionut Anghel (I)

Computer Science Department, Technical University of Cluj-Napoca, Memorandumului 28, 400114 Cluj-Napoca, Romania.

Ioan Salomie (I)

Computer Science Department, Technical University of Cluj-Napoca, Memorandumului 28, 400114 Cluj-Napoca, Romania.

Classifications MeSH