An analysis of anonymity in bitcoin using P2P network traffic

Philip Koshy, Diana Koshy, Patrick McDaniel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

297 Scopus citations

Abstract

 Over the last 4 years, Bitcoin, a decentralized P2P cryptocurrency, has gained widespread attention. The ability to create pseudoanonymous financial transactions using bitcoins has made the currency attractive to users who value their privacy. Although previous work has analyzed the degree of anonymity Bitcoin offers using clustering and flow analysis, none have demonstrated the ability to map Bitcoin addresses directly to IP data. We propose a novel approach to creating and evaluating such mappings solely using real-time transaction traffic collected over 5 months. We developed heuristics for identifying ownership relationships between Bitcoin addresses and IP addresses. We discuss the circumstances under which these relationships become apparent and demonstrate how nearly 1,000 Bitcoin addresses can be mapped to their likely owner IPs by leveraging anomalous relaying behavior.

Original languageEnglish (US)
Title of host publicationFinancial Cryptography and Data Security - 18th International Conference, FC 2014, Revised Selected Papers
EditorsReihaneh Safavi-Naini, Nicolas Christin
PublisherSpringer Verlag
Pages469-485
Number of pages17
ISBN (Electronic)9783662454718
DOIs
StatePublished - 2014
Event18th International Conference on Financial Cryptography and Data Security, FC 2014 - Christ Church, Barbados
Duration: Mar 3 2014Mar 7 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8437
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other18th International Conference on Financial Cryptography and Data Security, FC 2014
Country/TerritoryBarbados
CityChrist Church
Period3/3/143/7/14

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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