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Blockchain technology has been recognized as an innovative and effective means to improve transparency, security, and efficiency in the financial sector. However, privacy issues and reduction of efficiency have challenged large-scale applications the most. This issue motivates the current study that proposes a zero-knowledge proof (ZKP)-based Hyperledger Fabric framework that will ensure secure and privacy-preserving financial transaction processing. With the combination of the ZKP methods and smart contracts, the confidentiality of transactions will be verified, but at the same time, there will be audits and fraud detection. The PaySim1 synthetic financial transaction dataset, which contains more than six million records, will serve for the simulation and evaluation of different realistic workloads. The results of the experiments indicate that the ZKP-enabled framework can process 80.07 TPS on average with 0.01249 s of average latency, providing a privacy score over 98% at the same time, which reflects the effectiveness of zero-knowledge proofs in protecting sensitive transaction details while still enabling accurate verification and auditability within the blockchain network. Although the throughput is lower than that of a standard blockchain network (998,406 TPS), the given framework detects all the fraud cases at a 1.78% false positive rate, thus making sure that the system is both secure and compliant. This reduction is primarily due to the additional cryptographic overhead introduced by ZKP generation and verification, representing a trade-off between enhanced privacy and transaction processing speed. Additionally, the different setups were compared with each other in terms of privacy, efficiency, and resource utilization, and the optimized ones performed well in terms of these three aspects. To sum up the experiment, ZKP and Hyperledger Fabric, when jointly applied, not only increased the privacy and trust factors in the financial systems but also created the possibility to have very good operating conditions that are suitable for the applications.
Bowen Zheng (Thu,) studied this question.