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Poster: Privacy-Preserving Billing for Local Energy Markets

Authors: Alqahtani, Eman; Mustafa, Mustafa;

Poster: Privacy-Preserving Billing for Local Energy Markets

Abstract

We propose a privacy-preserving billing protocol for local energy markets (PBP-LEMs) that takes into account market participants' energy volume deviations from their bids. It enables a group of market entities to jointly compute participants’ bills in a decentralized and privacy-preserving manner. It also mitigates risks on individuals’ privacy arising from any potential internal collusion. We first propose a novel, efficient, and privacy-preserving individual billing scheme, achieving information-theoretic security, which serves as a building block. PBP-LEMs utilises this scheme, along with other techniques such as multiparty computation, Pedersen commitments and inner product functional encryption, to ensure data confidentiality and accuracy. We present three approaches, resulting in different levels of privacy and performance. We also show that PBP-LEMs is feasible for deployment in real LEMs.

Country
United Kingdom
Related Organizations
Keywords

MPC, Privacy, Security, LEM

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green