Linking NFT Transaction Events to Identify Privacy Risks

Abstract

Non-fungible tokens (NFTs) are unique tokens with various domains, e.g. real estate, metaverse, gaming and public auctions. However, when minted on public blockchains, the underlying blockchain transaction data can be publicly accessible. This instigated transaction data analysis for various purposes, including cryptocurrency price prediction and NFT market analysis. The public data may be considered privacy-sensitive which sets a barrier to the wider adoption of NFTs. In this work, we present that the analysis of the transaction events can describe activities in NFT applications by establishing connections between transactions and thereby, it can identify information that may be privacy-sensitive. This can be useful in developing suitable privacy-enhancing methods for NFTs. We collected transaction data from a blockchain-based game called Planet IX that was built on the Polygon blockchain and used graph visualisation to provide examples for constructed connections.