Evaluating User Privacy in Bitcoin

By Elli Androulaki, Ghassan O. Karame, Marc Roeschlin, T. Scherer, Srdjan Čapkun. 2013

735 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Sociology and Political Science

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Citations in the corpus

Bulletproofs: Short Proofs for Confidential Transactions and More (2018, background): “While the original Bitcoin paper [48] claimed that Bitcoin would provide anonymity through pseudonymous addresses early work on Bitcoin showed that the anonymity is limited [50], [51].”
Mixcoin: Anonymity for Bitcoin with Accountable Mixes (2014, background): “Several recent papers have studied ways to link a user’s addresses to each other and to an external identity [2,19,24,26].”
Privacy-Preserving Solutions for Blockchain: Review and Challenges (2019, background): “issues [10]–[12], which undermine user anonymity, confidentiality and privacy control in their transactions on the”
Bitcoin and Beyond: A Technical Survey on Decentralized Digital Currencies (2016, background): “Along these lines, there is a significant body of research on the analysis of Bitcoin’s publicly available block chain [34], [73]–[75], [89], [154]–[157].”
Secure High-Rate Transaction Processing in Bitcoin (2015, background): “Other works on Bitcoin have looked at its privacy aspects [13, 5], including analysis of its transaction graph [14] which allows to de-anonymize some of its users.”
Price Fluctuations and the Use of Bitcoin: An Empirical Inquiry (2015, neutral): “Within this literature, a large contingent is composed of studies that analyze the transaction records held in the blockchain [4, 107, 117, 118].”
On the Instability of Bitcoin Without the Block Reward (2016, background): “Some simulators are aimed at aspects of Bitcoin aside from strategic mining, such as privacy [3], or the peer-to-peer network [16].”
Sex, Drugs, and Bitcoin: How Much Illegal Activity Is Financed through Cryptocurrencies? (2019, background): “Another related, although small, branch of literature examines the degree of anonymity in bitcoin by quantifying the extent to which various algorithms can identify entities/users in bitcoin blockchain data and track their activity (e.g., Meiklejohn et al. 2013; Ron and Shamir 2013; Androulaki et al”
Security and Privacy in Decentralized Energy Trading Through Multi-Signatures, Blockchain and Anonymous Messaging Streams (2018, background): “A9 Distinguishability of the profiles Attacker can connect identities to addresses by tracing transfer history of a token in a block chain [18] [19].”
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.”
A fistful of bitcoins: characterizing payments among men with no names (2013, methodology): “The first heuristic we use, in which we link input addresses together, has already been used many times in previous work [2, 17, 18, 21]; for completeness, we nevertheless present it here.”
Bitcoin mining and its energy footprint (2014, background): “[2], as well as attempts to gain insights into is behind transactions e.”
Bitcoin (2015, background): “This helps restore privacy to some extent, but some information is always leaked even when Bitcoin addresses are not reused.(3,20,27) The mixture of partial privacy and transparency within Bitcoin has led to interesting innovations.”
SoK: Research Perspectives and Challenges for Bitcoin and Cryptocurrencies (2015, background): “change output is controlled by a single entity” [4] and “an address is used at most once as change” [75] can also be utilized by an adversary to link together different addresses controlled by the same entity.”
Is Bitcoin Really Untethered? (2020, neutral): “To reduce the complexity of the network, we adopt methods from computer science literature [Androulaki et al. (2013), Meiklejohn et al.”