Heuristic-Based Address Clustering in Cardano Blockchain

Hello Cardano Community,

We’d like to bring to your attention a significant event - the Cardano Foundation’s collaborative initiative with the University of Zurich. This partnership marked a crucial step towards our ongoing commitment to promoting education and facilitating research in the field of blockchain technology.

The full details of this collaboration can be revisited in the article here: A Commitment to Education: the Cardano Foundation strengthens ties with the University of Zurich

One of the pivotal outcomes of this strengthened alliance is a research paper titled “Heuristic-Based Address Clustering in Cardano Blockchain”. This academic piece delves into heuristic-based methods for address clustering on the Cardano blockchain.


“Blockchain technology has recently gained widespread popularity as a practical method of storing immutable data while preserving the privacy of users by anonymizing their real identities. This anonymization approach, however, significantly complicates the analysis of blockchain data. To address this problem, heuristic-based clustering algorithms as an effective way of linking all addresses controlled by the same entity have been presented in the literature. In this paper, considering the particular features of the Extended Unspent Transaction Outputs accounting model introduced by the Cardano blockchain, two new clustering heuristics are proposed for clustering the Cardano payment addresses. Applying these heuristics and employing the UnionFind algorithm, we efficiently cluster all the addresses that have appeared on the Cardano blockchain from September 2017 to January 2023, where each cluster represents a distinct unique entity. The results show that each medium-sized entity in the Cardano network owns and controls 9.67 payment addresses on average. The results also confirm that a power law distribution is fitted to the distribution of entity sizes recognized using our proposed heuristics.”

Attached to this post is the full research paper in PDF format for anyone who wishes to delve deeper into the findings and methods of this study.

Cardano_paper_ChainScience_2023.pdf (589.2 KB)

Your feedback and thoughts on this paper are highly appreciated. We’re looking forward to a lively and informative discussion. Please, share your insights, questions, or any points of clarity you might need in the comments below.