Safeguarding the Unseen: a Study on Data Privacy in DeFi Protocols
Zhuangtong Huang, Jiawei Zhu, Zhongyu Huang, Yixin Xu, Jerome Yen and, Ye Wang

TL;DR
This paper proposes a novel privacy-preserving protocol for DeFi that combines homomorphic encryption and zero-knowledge proofs to protect sensitive user data while maintaining data availability and decentralization.
Contribution
It introduces a new protocol integrating advanced cryptographic techniques to enhance privacy and efficiency in DeFi platforms, addressing a key challenge in blockchain data access.
Findings
The protocol effectively safeguards user privacy in DeFi transactions.
It improves capital efficiency in DeFi markets.
The methods are applicable to cross-border financial applications.
Abstract
The financial sector's adoption of technology-driven data analysis has enhanced operational efficiency and revenue generation by leveraging personal sensitive data. However, the inherent characteristics of blockchain hinder decentralized finance (DeFi) from accessing necessary sensitive user data. To address this challenge, we introduce a protocol that both safeguards user privacy and ensures data availability through the incorporation of homomorphic encryption and zero-knowledge-proof techniques in blockchain technology. This novel protocol helps mitigate privacy risks caused by sensitive data leaks while improving the capital efficiency of the DeFi market. Furthermore, we explore the applicability of these privacy-preserving methods in on-chain ecosystems and cross-border financial applications. Our solution contributes to secure, user-centric solutions for DeFi while upholding…
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Taxonomy
TopicsBlockchain Technology Applications and Security · FinTech, Crowdfunding, Digital Finance · Privacy, Security, and Data Protection
