2024/03/01 by Hugo Schnoering, Schnoering, Hugo, Pierre Porthaux +3
Computer Science · #Blockchain Technology Applications and Security #Caching and Content Delivery #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #FOS: Economics and business #General Finance (q-fin.GN) #Peer-to-Peer Network Technologies #Social and Information Networks (cs.SI)
paper · pdf · doi:10.48550/arxiv.2403.00523
openalex publication_date 2024/03/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Exploring transactions within the Bitcoin blockchain entails examining the transfer of bitcoins among several hundred million entities. However, it is often impractical and resource-consuming to study such a vast number of entities. Consequently, entity clustering serves as an initial step in most analytical studies. This process often employs heuristics grounded in the practices and behaviors of these entities. In this research, we delve into the examination of two widely used heuristics, alongside the introduction of four novel ones. Our contribution includes the introduction of the clustering ratio, a metric designed to quantify the reduction in the number of entities achieved by a given heuristic. The assessment of this reduction ratio plays an important role in justifying the selection of a specific heuristic for analytical purposes. Given the dynamic nature of the Bitcoin system, characterized by a continuous increase in the number of entities on the blockchain, and the evolving behaviors of these entities, we extend our study to explore the temporal evolution of the clustering ratio for each heuristic. This temporal analysis enhances our understanding of the effectiveness of these heuristics over time.