TY - GEN
T1 - Blockchain-Based Random Selection Among a Private Number of Candidates
AU - Gamiz, Idoia
AU - Regueiro, Cristina
AU - Jacob, Eduardo
AU - Lage, Oscar
AU - Unzilla, Juanjo
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - Random selection processes are fundamental across diverse domains, requiring transparency and fairness in execution. However, some contexts, such as sensitive ecosystems like healthcare or education, also require an additional degree of privacy by avoiding information leakage about the number of candidates for the selection. Despite this, existing literature lacks comprehensive solutions that maintain this privacy while upholding transparency and fairness. To address this gap, the study proposes a platform that combines blockchain and Homomorphic Encryption. The main contributions include a detailed definition of the architecture and the operational procedures, and an in-depth exploration of the proposed Random Number Generator function. The study introduces a homomorphic approach for confidentially computing candidate counts and explores methods for homomorphically constraining random numbers within a private range. By combining blockchain and Homomorphic Encryption, this research offers a robust solution for transparent and fair random selection while maintaining the number of candidates private.
AB - Random selection processes are fundamental across diverse domains, requiring transparency and fairness in execution. However, some contexts, such as sensitive ecosystems like healthcare or education, also require an additional degree of privacy by avoiding information leakage about the number of candidates for the selection. Despite this, existing literature lacks comprehensive solutions that maintain this privacy while upholding transparency and fairness. To address this gap, the study proposes a platform that combines blockchain and Homomorphic Encryption. The main contributions include a detailed definition of the architecture and the operational procedures, and an in-depth exploration of the proposed Random Number Generator function. The study introduces a homomorphic approach for confidentially computing candidate counts and explores methods for homomorphically constraining random numbers within a private range. By combining blockchain and Homomorphic Encryption, this research offers a robust solution for transparent and fair random selection while maintaining the number of candidates private.
KW - Blockchain
KW - Homomorphic Encryption
KW - Privacy
KW - Selection
UR - http://www.scopus.com/inward/record.url?scp=85210178577&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-75016-8_1
DO - 10.1007/978-3-031-75016-8_1
M3 - Conference contribution
AN - SCOPUS:85210178577
SN - 9783031750151
T3 - Lecture Notes in Networks and Systems
SP - 3
EP - 14
BT - International Joint Conferences - 17th International Conference on Computational Intelligence in Security for Information Systems CISIS 2024 and 15th International Conference on European Transnational Education ICEUTE 2024
A2 - Quintián, Héctor
A2 - Jove, Esteban
A2 - Corchado, Emilio
A2 - Troncoso Lora, Alicia
A2 - Martínez Álvarez, Francisco
A2 - Pérez García, Hilde
A2 - Calvo Rolle, José Luis
A2 - Martínez de Pisón, Francisco Javier
A2 - García Bringas, Pablo
A2 - Herrero Cosío, Álvaro
A2 - Fosci, Paolo
PB - Springer Science and Business Media Deutschland GmbH
T2 - 17th International Conference on Computational Intelligence in Security for Information Systems, CISIS 2024 and the 15th International Conference on EUropean Transnational Education, ICEUTE 2024
Y2 - 8 October 2024 through 10 October 2024
ER -