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BP-Vot: Blockchain-Based e-Voting Using Smart Contracts, Differential Privacy, and Self-Sovereign Identities | IEEE Journals & Magazine | IEEE Xplore

BP-Vot: Blockchain-Based e-Voting Using Smart Contracts, Differential Privacy, and Self-Sovereign Identities


The proposed BP-Vot system utilizes Smart Contracts, a standardized SSI-framework, and a novel Differential Privacy mechanism for realizing a privacy-preserving Blockchai...

Abstract:

Election is the key process typically utilized for maintaining democracy in a given society. Recent technological advancements, such as Blockchain (BC), have been already...Show More

Abstract:

Election is the key process typically utilized for maintaining democracy in a given society. Recent technological advancements, such as Blockchain (BC), have been already deployed in previous works to realize non-conventional e-Voting systems. The main goal for such proposals is to provide the necessary level of security and reliability, while maintaining transparency, trust, and remote elections. However, the distributed and publicity nature of BC brought new challenges related to privacy and performance trade-off. This paper aims to address these issues by integrating smart contracts for reliability and transparency, Differential Privacy for enhancing vote anonymity, and Self-Sovereign Identities to unlock the potential of the Web3 framework for verifiable credentials and digital identities. Specifically, a novel ( k,\epsilon )-differential privacy mechanism is developed, where a randomly selected candidate is pivoted from which retrievable votes are transferred to other candidates. Final election results are then statistically approximated. We evaluate the proposed methods for different arrival rates (10–80 TX/s), different total numbers of cast votes (10k–50k votes), and different numbers of elected candidates (2–8 candidates). To demonstrate the applicability of our proposal in real-life scenarios, we deploy our SC on a cloud-based permissioned BC network using Hyperledger Besu, with nodes set in Google’s EU and USA data centers. Our experimental results showed that BP-Vot could provide 24% enhancement in latency over state-of-the-art solutions ( \approx 1 s/TX compared to 1.24 s/TX). Additionally, using a standardized Min-Max regression mechanism, we show that BP-Vot could provide no less than 98% accuracy in votes approximation during all experiments, with a linearly increasing accuracy trend as a function of the total number of cast votes. Finally, we formally evaluate the proposed differential privacy method and prove that it is robust against reconst...
The proposed BP-Vot system utilizes Smart Contracts, a standardized SSI-framework, and a novel Differential Privacy mechanism for realizing a privacy-preserving Blockchai...
Published in: IEEE Access ( Volume: 13)
Page(s): 46106 - 46123
Date of Publication: 05 March 2025
Electronic ISSN: 2169-3536

Funding Agency:

Author image of Hamza Baniata
Department of Software Engineering, University of Szeged, Szeged, Hungary
Hamza Baniata received the M.Sc. degree (Hons.) in computer science from the University of Jordan, Jordan, in 2018, and the Ph.D. degree (Hons.) in computer science from the University of Szeged, Hungary, in 2023.
He is currently an Assistant Professor with the Department of Software Engineering, University of Szeged. Since 2019, he has been with the IoT-Cloud Research Group of the Department. He is an Expert in the integr...Show More
Hamza Baniata received the M.Sc. degree (Hons.) in computer science from the University of Jordan, Jordan, in 2018, and the Ph.D. degree (Hons.) in computer science from the University of Szeged, Hungary, in 2023.
He is currently an Assistant Professor with the Department of Software Engineering, University of Szeged. Since 2019, he has been with the IoT-Cloud Research Group of the Department. He is an Expert in the integr...View more
Author image of Giovanny Caluna
Department of Software Engineering, University of Szeged, Szeged, Hungary
Giovanny Caluna received the B.Eng. degree in information technology from Yachay Tech University, Ecuador, in 2020, and the M.Sc. degree in computer science from the University of Szeged, Hungary, in 2024. His professional expertise focuses on software development, with a specialization in cloud computing, AI/ML, and blockchain technologies. His research encompasses the application of convolutional neural networks for pla...Show More
Giovanny Caluna received the B.Eng. degree in information technology from Yachay Tech University, Ecuador, in 2020, and the M.Sc. degree in computer science from the University of Szeged, Hungary, in 2024. His professional expertise focuses on software development, with a specialization in cloud computing, AI/ML, and blockchain technologies. His research encompasses the application of convolutional neural networks for pla...View more

Author image of Hamza Baniata
Department of Software Engineering, University of Szeged, Szeged, Hungary
Hamza Baniata received the M.Sc. degree (Hons.) in computer science from the University of Jordan, Jordan, in 2018, and the Ph.D. degree (Hons.) in computer science from the University of Szeged, Hungary, in 2023.
He is currently an Assistant Professor with the Department of Software Engineering, University of Szeged. Since 2019, he has been with the IoT-Cloud Research Group of the Department. He is an Expert in the integration of several trending technologies, including blockchain, fog computing, machine learning, and the Internet of Things (IoT), for which he has published several high-quality articles in top scientific journals. He has been an active participant in several (inter) national projects, including the Swarmchestrate EU Horizon Project, Fog-Block4Trust sub-grant of the TruBlo EU H2020 project, the CERCIRAS EU Cost Action, the Research Excellence Scholarship Program (EKÖP-24), MILAB, and the OTKA FK 131793 project. He also serves as the chair, a PC member, and a reviewer for several internationally recognized conferences, workshops, and top-tier scientific journals. According to the Scientometrics of Hungarian researchers, he is nationally recognized as a top researcher (D1) in his category.
Hamza Baniata received the M.Sc. degree (Hons.) in computer science from the University of Jordan, Jordan, in 2018, and the Ph.D. degree (Hons.) in computer science from the University of Szeged, Hungary, in 2023.
He is currently an Assistant Professor with the Department of Software Engineering, University of Szeged. Since 2019, he has been with the IoT-Cloud Research Group of the Department. He is an Expert in the integration of several trending technologies, including blockchain, fog computing, machine learning, and the Internet of Things (IoT), for which he has published several high-quality articles in top scientific journals. He has been an active participant in several (inter) national projects, including the Swarmchestrate EU Horizon Project, Fog-Block4Trust sub-grant of the TruBlo EU H2020 project, the CERCIRAS EU Cost Action, the Research Excellence Scholarship Program (EKÖP-24), MILAB, and the OTKA FK 131793 project. He also serves as the chair, a PC member, and a reviewer for several internationally recognized conferences, workshops, and top-tier scientific journals. According to the Scientometrics of Hungarian researchers, he is nationally recognized as a top researcher (D1) in his category.View more
Author image of Giovanny Caluna
Department of Software Engineering, University of Szeged, Szeged, Hungary
Giovanny Caluna received the B.Eng. degree in information technology from Yachay Tech University, Ecuador, in 2020, and the M.Sc. degree in computer science from the University of Szeged, Hungary, in 2024. His professional expertise focuses on software development, with a specialization in cloud computing, AI/ML, and blockchain technologies. His research encompasses the application of convolutional neural networks for plant disease classification and the performance optimization of matrix multiplication algorithms, leveraging the Quinde I supercomputer in Ecuador.
Giovanny Caluna received the B.Eng. degree in information technology from Yachay Tech University, Ecuador, in 2020, and the M.Sc. degree in computer science from the University of Szeged, Hungary, in 2024. His professional expertise focuses on software development, with a specialization in cloud computing, AI/ML, and blockchain technologies. His research encompasses the application of convolutional neural networks for plant disease classification and the performance optimization of matrix multiplication algorithms, leveraging the Quinde I supercomputer in Ecuador.View more

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