Quantitative Analysis of the Full Bitcoin Transaction Graph

By Dorit Ron, Adi Shamir. 2013

1,040 citations recorded by the source corpus.

Subfields: Information Systems, Statistical and Nonlinear Physics, Transportation

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In Statistical and Nonlinear Physics

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Citations in the corpus

Ekiden: A Platform for Confidentiality-Preserving, Trustworthy, and Performant Smart Contracts (2018, neutral): “As numerous studies have shown [64], [53], [56], [65], pseudonymity provides only weak privacy protection.”
Is Bitcoin Really Untethered? (2020, positive): “In particular, because of the semi-transparent nature of the transaction history recorded on the blockchain, we are able to use variants of methods developed in computer science [Meiklejohn et al. (2013) and Ron and Shamir (2013)] to cluster groups of related Bitcoin wallets.”
An Overview on Smart Contracts: Challenges, Advances and Platforms (2019, neutral): “As shown in [87], it is possible to obtain useful information from the transaction data based on the transactional graph analysis.”
Deanonymisation of Clients in Bitcoin P2P Network (2014, background): “would be totally unachievable via transaction graph analysis [11, 15].”
The Economics of Bitcoin Mining, or Bitcoin in the Presence of Adversaries (2013, background): “Such an analysis is necessary but not sufficient to explain the consensus that Bitcoins are valuable.”
GraphPIM: Enabling Instruction-Level PIM Offloading in Graph Computing Frameworks (2017, methodology): “In our experiment, the input data is a Bitcoin transaction graph [38], in which each vertex represents a Bitcoin account and each edge represents a Bitcoin transaction.”
Privacy-Preserving Solutions for Blockchain: Review and Challenges (2019, background): “Although users of public blockchains can create new public addresses independently, the ledger keeps track of all their history in blockchain transactions graphs that link all independent public key addresses to the user [60]–[64].”
Zerocoin: Anonymous Distributed E-Cash from Bitcoin (2013, background): “Bitcoin, on the other hand, is a viable digital currency with a market capitalization valued at more than $100 million [1] and between $2 and $5 million USD in transactions a day [2].”
A systematic literature review of blockchain-based applications: Current status, classification and open issues (2019, neutral): “For instance, there are de-anonymisation approaches which analyse transactional graph structures of cryptocurrencies (Meiklejohn et al., 2013; Ron and Shamir, 2013).”
zkLedger: Privacy-Preserving Auditing for Distributed Ledgers (2018, background): “The transaction graph alone leaks substantial information [36, 38, 45, 46]; for example, the FBI followed linked transactions to trace bitcoins and used this as evidence in court [28].”
Zether: Towards Privacy in a Smart Contract World (2020, background): “In the two most popular cryptocurrencies, Bitcoin [59] and Ethereum [17], for instance, not only are the transaction amounts fully visible in the clear but users can also be de-anonymized [22,31,55,71]”
Secure Multiparty Computations on Bitcoin (2014, background): “Although, as argued in the extended version of this paper, it may actually make economic sense to use our protocols in practice, we view gambling mostly as a motivating example for introducing a concept that can be called “MPCs on Bitcoin,” and which will hopefully have other applications.”
A Survey on Information and Communication Technologies for Industry 4.0: State-of-the-Art, Taxonomies, Perspectives, and Challenges (2019, background): “While pseudonimity on the Blockchain is supported out-ofthe-box, maintaining anonymity and privacy is much harder, as all the transactions appear on the shared data structure to be verifiable [301].”