arXiv subjects

Eman Alqahtani

Publications and source records attributed to Eman Alqahtani.

3 recordsLinked to original sources

arXiv2026

Privacy-Preserving Local Energy Trading Considering Network Fees

Driven by the widespread deployment of distributed energy resources, local energy markets (LEMs) have emerged as a promising approach for enabling direct trades among prosumers and consumers to balance intermittent generation and demand locally. However, LEMs involve processing sensitive participant data, which, if not protected, poses privacy risks. At the same time, since electricity is exchanged over the physical power network, market mechanisms should consider physical constraints and network-related costs. Existing work typically addresses these issues separately, either by incorporating grid-related aspects or by providing privacy protection. To address this gap, we propose a privacy-preserving protocol for LEMs, with consideration of network fees that can incite participants to respect physical limits. The protocol is based on a double-auction mechanism adapted from prior work to enable more efficient application of our privacy-preserving approach. To protect participants' data, we use secure multiparty computation. In addition, Schnorr's identification protocol is employed with multiparty verification to ensure authenticated participation without compromising privacy. We further optimise the protocol to reduce communication and round complexity. We prove that the protocol meets its security requirements and show through experimentation its feasibility at a typical LEM scale: a market with 5,000 participants can be cleared in 4.17 minutes.

cs.CR↗

arXiv2024

Privacy-Preserving Billing for Local Energy Markets

We propose a privacy-preserving billing protocol for local energy markets (PBP-LEM) that takes into account market participants' energy volume deviations from their bids. PBP-LEM enables a group of market entities to jointly compute participants' bills in a decentralized and privacy-preserving manner without sacrificing correctness. It also mitigates risks on individuals' privacy arising from any potential internal collusion. We first propose an efficient and privacy-preserving individual billing scheme, achieving information-theoretic security, which serves as a building block. PBP-LEM utilizes this scheme, along with other techniques such as multiparty computation, inner product functional encryption and Pedersen commitments to ensure data confidentiality and accuracy. Additionally, we present three approaches, resulting in different levels of privacy protection and performance. We prove that the protocol meets its security and privacy requirements and is feasible for deployment in real LEMs: bills can be computed in less than five minutes for 4,000 users using the most computationally intensive approach, and in just 0.18 seconds using the least intensive one.

cs.CR↗

arXiv2023

Zone-Based Privacy-Preserving Billing for Local Energy Market Based on Multiparty Computation

This paper proposes a zone-based privacy-preserving billing protocol for local energy markets that takes into account energy volume deviations of market participants from their bids. Our protocol incorporates participants' locations on the grid for splitting the deviations cost. The proposed billing model employs multiparty computation so that the accurate calculation of individual bills is performed in a decentralised and privacy-preserving manner. We also present a security analysis as well as performance evaluations for different security settings. The results show superiority of the honest-majority model to the dishonest majority in terms of computational efficiency. They also show that the billing can be executed for 5000 users in less than nine seconds in the online phase for all security settings, demonstrating its feasibility to be deployed in real local energy markets.

cs.CR↗