The Complex Community Structure of the Bitcoin Address Correspondence Network
@inproceedings{Fischer2021TheCC, title={The Complex Community Structure of the Bitcoin Address Correspondence Network}, author={Jan A. Fischer and Andres Palechor and D. Dell'Aglio and Abraham Bernstein and Claudio J. Tessone}, booktitle={Frontiers in Physics}, year={2021} }
Bitcoin is built on a blockchain, an immutable decentralized ledger that allows entities (users) to exchange Bitcoins in a pseudonymous manner. Bitcoins are associated with alpha-numeric addresses and are transferred via transactions. Each transaction is composed of a set of input addresses (associated with unspent outputs received from previous transactions) and a set of output addresses (to which Bitcoins are transferred). Despite Bitcoin was designed with anonymity in mind, different…
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References
SHOWING 1-10 OF 48 REFERENCES
Automatic Bitcoin Address Clustering
- Computer Science2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA)
- 2017
This paper proposes to use off-chain information as votes for address separation and to consider it together with blockchain information during the clustering model construction step, showing the feasibility of a proposed approached for Bitcoin address clustering.
Heuristic-Based Address Clustering in Bitcoin
- Computer Science, BusinessIEEE Access
- 2020
A new heuristic that detects one-time change addresses by eliminating addresses that are reused later as non-change addresses is proposed, which works for transactions whose one- time change addresses cannot be identified by the previous two heuristics.
From Bitcoin to Bitcoin Cash: a network analysis
- Computer ScienceCRYBLOCK@MobiSys
- 2018
Results suggest that the principle known as 'fittest-gets-richer', combined with a continuous increasing of connections, might constitute the mechanism leading these networks to reach their current structure.
Bitcoin Transaction Networks: An Overview of Recent Results
- Computer ScienceFrontiers in Physics
- 2020
Some recent results concerning the structural properties of the Bitcoin Transaction Networks are reviewed, a generic name referring to a set of three different constructs: the Bitcoin Address Network, the Bitcoin User Network, and the Bitcoin Lightning Network.
Bitcoin Transaction Graph Analysis
- Computer Science, MathematicsArXiv
- 2015
This work annotates the public transaction graph by linking bitcoin public keys to "real" people - either definitively or statistically - and runs the annotated graph through a graph-analysis framework to find and summarize activity of both known and unknown users.
Breaking Bad: De-Anonymising Entity Types on the Bitcoin Blockchain Using Supervised Machine Learning
- Computer ScienceHICSS
- 2018
This paper presents a novel approach for reducing the anonymity of the Bitcoin Blockchain by using Supervised Machine Learning to predict the type of yet-unidentified entities, and finds that it can indeed predict thetype of a yet- unidentified entity.
Deanonymization and Linkability of Cryptocurrency Transactions Based on Network Analysis
- Computer Science, Mathematics2019 IEEE European Symposium on Security and Privacy (EuroS&P)
- 2019
It is argued that timings of transaction messages leak information about their origin, which can be exploited by a well connected adversarial node, and a novel technique for linking transactions based on transaction propagation analysis is proposed.
The evolving liaisons between the transaction networks of Bitcoin and its price dynamics
- Computer Science
- 2019
This paper analyses the properties of the transaction network of Bitcoin and reveals the interplay between structural quantities, indicative of the collective behaviour of Bitcoin users, and price movements, showing that, during price drops, the system is characterised by a larger heterogeneity of nodes activity.
Do Bitcoin Users Really Care About Anonymity? An Analysis of the Bitcoin Transaction Graph
- Computer Science2018 IEEE International Conference on Big Data (Big Data)
- 2018
This paper demystifies this doubt via analyzing the Bitcoin transaction graphs with the following three contributions: it outlines three representative metrics that can signify whether users concern about anonymity, and examines the collective trend of anonymity concerns from a macroscope.
Data-Driven De-Anonymization in Bitcoin
- Computer Science
- 2015
The results demonstrate that even modern wallet software can not protect its users properly, and it is shown that this metric can be further improved by combining several more sophisticated heuristics.