Detecting Wash Trading in Non-Fungible Token (NFT) Markets

Blockchain technology has revolutionized the way we think about data storage and analysis. However, dealing with sensitive information on a blockchain can be challenging due to issues of privacy and linkability. In this article, we propose a novel approach called Linkability Networks, which enables privacy-preserving data analysis while maintaining the integrity of the blockchain ecosystem.
Linkability Networks are directed graphs that represent potential connections between blockchain accounts. Each vertex in the graph represents an account, and edges connecting them indicate a relationship between the accounts. By analyzing these relationships, we can identify patterns and trends in the data without revealing sensitive information about individual users.
Our approach leverages the concept of linkability, which is the capacity to distinguish whether two or more items of interest are related within a system. In the context of blockchains, linkability refers to the ability to identify connections between accounts without disclosing their personal information. By creating a Linkability Network, we can effectively illustrate these potential connections and analyze the data without compromising privacy.
The Linkability Network is constructed using a directed graph, where each vertex represents an account and edges represent shortest paths of ETH currency transfer between accounts. The weight of each edge is determined by the length of the path, which allows us to prioritize edges based on their significance. This approach enables efficient data analysis while maintaining the privacy of individual users.
In summary, Linkability Networks offer a powerful tool for privacy-preserving data analysis on blockchains. By leveraging the concept of linkability, we can create graphical representations that highlight potential connections between accounts without revealing sensitive information. This approach has significant implications for various industries, including finance, healthcare, and social media, where data privacy is a critical concern.