Stealthy Clustering of Ethereum Transactions Using Time Leakage from Fixed Nodes

Congcong Yu, Chengpu Jiang, Chen Yang, Meng Shen*, Lie Huang Zhu, Zheng Che

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

In recent years, data mining with users as entities has become a fundamental tool for digital currency investigations. In Ethereum, researchers can perform transaction clustering based on users' behavioral habits and usage patterns in specific scenarios. However, the major shortcoming of these technologies is that they cover only a small fraction compared to the huge number of transactions. In this paper, we propose a stealthy clustering of Ethereum transactions using time leakage from fixed nodes (CIFO), which is applied to all transactions, while also being stealthy and difficult to detect. Leveraging timestamps relayed from N fixed nodes, CIFO can better describe the network properties of transactions, in compared with the first N timestamps. The experimental results show that CIFO can determine whether two transactions enter the network from the same source with the precision of 87%.

Original languageEnglish
Title of host publicationProceedings - 2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops, ICDCSW 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7-12
Number of pages6
ISBN (Electronic)9781665488792
DOIs
Publication statusPublished - 2022
Event42nd IEEE International Conference on Distributed Computing Systems Workshops, ICDCSW 2022 - Bologna, Italy
Duration: 10 Jul 202213 Jul 2022

Publication series

NameProceedings - 2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops, ICDCSW 2022

Conference

Conference42nd IEEE International Conference on Distributed Computing Systems Workshops, ICDCSW 2022
Country/TerritoryItaly
CityBologna
Period10/07/2213/07/22

Keywords

  • Blockchain
  • Ethereum
  • data mining
  • network analysis
  • transactions clustering

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