UPDF AI

An Analysis of Zero-knowledge Proof-based Privacy-preserving Techniques for Non-fungible Tokens in the Metaverse

Dorottya Zelenyanszki,Zhé Hóu,Kamanashis Biswas,V. Muthukkumarasamy

2023 · DOI: 10.1109/MetaCom57706.2023.00119
3 Citations

Abstract

Non-fungible tokens (NFTs) have huge potential to be included in metaverse-related applications such as digital ownership management and asset trading. However, existing research identified that privacy-preserving techniques and methods are essential for NFTs for large-scale adoption in the metaverse. This paper conducted an analysis of several existing research works that mainly use zero-knowledge proofs (ZKPs) and/or commitments to protect privacy for blockchain applications. Based on the results of this comparative analysis, we deducted several assumptions. This paper identifies the potential next steps to design new privacy-preserving techniques that will enable privacy-aware metaverse users to leverage the maximal benefits of the NFTs.