Description
TL;DR: A deanonymization study combining more than one hundred monitoring clients with a Bayesian model of Bitcoin transaction propagation.
About This Document
Péter L. Juhász, József Stéger, Dániel Kondor, and Gábor Vattay observe Bitcoin network messages over two months and construct a probabilistic model for associating addresses and transactions with clients and geographic locations. The paper describes its measurement deployment, inference method, and experimental results.
Why Bitcoin People May Care
Bitcoin's ledger is pseudonymous, while its peer-to-peer relay layer can leak additional identifying information. This paper is a period study of that intersection, not proof that every user can be identified or that the same attack works unchanged today. Network behavior, node software, routing, privacy tools, and adversary visibility evolve, so the 2016 assumptions matter.
What You Receive
Purchase reveals the verified preserved PDF location for this document.
Document Details
- Title: A Bayesian Approach to Identify Bitcoin Users
- Author / organization: Péter L. Juhász, József Stéger, Dániel Kondor, and Gábor Vattay
- Year: 2016
- Language: English
- Document type: Bitcoin privacy research paper
- Pages: 13
CacheRat provides researched source-location and document-identification information. CacheRat does not claim ownership of the underlying third-party documentation.
