TY - GEN
T1 - Account Clustering in the Polkadot Network
T2 - 5th IEEE International Conference on Blockchain and Cryptocurrency, ICBC 2023
AU - Caprolu, Maurantonio
AU - Di Pietro, Roberto
N1 - Funding Information:
ACKNOWLEDGMENTS This publication was partially supported by the Qatar National Research Fund (QNRF), a member of The Qatar Foundation, through the awards [NPRP-S-11-0109-180242] and [NPRP11C-1229-170007]. The information and views set out in this publication are those of the authors and do not necessarily reflect the official opinion of the QNRF.
Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - This paper investigates, for the first time, user account clustering in the Polkadot network, one of the most innovative account-based altcoins in the market. To achieve this goal, we levereged the 'deposit address reuse' heuristic on the Polkadot relay chain. In detail, we propose a novel deposit address detection methodology, combined with a general clustering strategy. To show the viability of our approach, we present a case study involving Binance and Kraken, the two major exchanges active in the Polkadot network. The analysis extends over a sensitive time window-starting from Polkadot genesis (May 2020) up to block 12,532,600 (October 2022). Thanks to the proposed methodology, we clustered more than 145,440 accounts belonging to exchanges, and more than 25,000 user accounts, representing around 25% of all the Binance/Kraken on-chain customers. The general applicability of our technique, the preliminary achieved results-showing both the viability and the value provided by our approach-, and the research hints discussed in the paper, also pave the way for further research in the field.
AB - This paper investigates, for the first time, user account clustering in the Polkadot network, one of the most innovative account-based altcoins in the market. To achieve this goal, we levereged the 'deposit address reuse' heuristic on the Polkadot relay chain. In detail, we propose a novel deposit address detection methodology, combined with a general clustering strategy. To show the viability of our approach, we present a case study involving Binance and Kraken, the two major exchanges active in the Polkadot network. The analysis extends over a sensitive time window-starting from Polkadot genesis (May 2020) up to block 12,532,600 (October 2022). Thanks to the proposed methodology, we clustered more than 145,440 accounts belonging to exchanges, and more than 25,000 user accounts, representing around 25% of all the Binance/Kraken on-chain customers. The general applicability of our technique, the preliminary achieved results-showing both the viability and the value provided by our approach-, and the research hints discussed in the paper, also pave the way for further research in the field.
KW - Account Clustering
KW - Blockchain
KW - Crypto Exchange
KW - Cryptocurrency
KW - Polkadot
UR - http://www.scopus.com/inward/record.url?scp=85166235520&partnerID=8YFLogxK
U2 - 10.1109/ICBC56567.2023.10174938
DO - 10.1109/ICBC56567.2023.10174938
M3 - Conference contribution
AN - SCOPUS:85166235520
T3 - 2023 IEEE International Conference on Blockchain and Cryptocurrency, ICBC 2023
BT - 2023 IEEE International Conference on Blockchain and Cryptocurrency, ICBC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 1 May 2023 through 5 May 2023
ER -