Charge Me Securely: Decentralized Privacy-Aware and Publicly Verifiable Energy Trading with Electric Vehicles

With the widespread adoption of electric vehicles (EVs), Vehicle-to-Vehicle (V2V) charging technology offers a more flexible solution for EV charging, significantly alleviating charging inconvenience, particularly in remote areas. However, the current V2V energy trading landscape lacks reliable management platforms with transparent transaction protocols. Furthermore, notable deficiencies exist in data privacy and security, which hinder the broader implementation of V2V charging services. Addressing these challenges, particularly the provision of secure and publicly auditable V2V charging without relying on centralized platforms or disclosing user privacy, has become a critical concern. For this reason, this paper presents PET, a decentralized Privacy-preserving Energy Trading system with public verifiability for EVs. PET is built upon the emerging blockchain technology to decentralize energy trading while ensuring accountability. We model energy demand-supply matching as range matching of locations and charge amounts between a buyer and sellers, and employ reverse auction to select the winner. For efficient and privacy-aware range proofs, we propose a novel batched hash chain-based range proof (BHW) primitive. In addition, PET integrates zk-SNARKs to verify payment correctness while maintaining user privacy. Our system supports public verifiability, entitling any third party to independently verify the transaction integrity. We analyze the privacy guarantees and public verifiability of PET. Extensive experiments implemented on Hyperledger Fabric further validate that PET delivers robust performance with a 4 × reduction in verification cost compared to that without batch proofs.

Authors

Institutions

Publication Details

Published
2024-12-02
DOI
https://doi.org/10.1109/secon64284.2024.10934907
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Charge Me Securely: Decentralized Privacy-Aware and Publicly Verifiable Energy Trading with Electric Vehicles

Haiqin Wu, Zhenfu Cao, Xiaolei Dong, Xiao Chen et al.
Blockchain Technology Applications and Security
article

Charge Me Securely: Decentralized Privacy-Aware and Publicly Verifiable Energy Trading with Electric Vehicles

Haiqin Wu, Zhenfu Cao, Xiaolei Dong, Xiao Chen, Jucai Yang
article en

Abstract

With the widespread adoption of electric vehicles (EVs), Vehicle-to-Vehicle (V2V) charging technology offers a more flexible solution for EV charging, significantly alleviating charging inconvenience, particularly in remote areas. However, the current V2V energy trading landscape lacks reliable management platforms with transparent transaction protocols. Furthermore, notable deficiencies exist in data privacy and security, which hinder the broader implementation of V2V charging services. Addressing these challenges, particularly the provision of secure and publicly auditable V2V charging without relying on centralized platforms or disclosing user privacy, has become a critical concern. For this reason, this paper presents PET, a decentralized Privacy-preserving Energy Trading system with public verifiability for EVs. PET is built upon the emerging blockchain technology to decentralize energy trading while ensuring accountability. We model energy demand-supply matching as range matching of locations and charge amounts between a buyer and sellers, and employ reverse auction to select the winner. For efficient and privacy-aware range proofs, we propose a novel batched hash chain-based range proof (BHW) primitive. In addition, PET integrates zk-SNARKs to verify payment correctness while maintaining user privacy. Our system supports public verifiability, entitling any third party to independently verify the transaction integrity. We analyze the privacy guarantees and public verifiability of PET. Extensive experiments implemented on Hyperledger Fabric further validate that PET delivers robust performance with a 4 × reduction in verification cost compared to that without batch proofs.

University of Leicester (GB), East China Normal University (CN)
Affordable and clean energy
Openalex Percentile: Top 54%
Blockchain Technology Applications and Security
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.