Mixcoin: Anonymity for Bitcoin with Accountable Mixes
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Mixing services are anonymous service providers that divide users' funds into smaller parts, randomly mix these parts to make users and transactions unlinkable, and allow users to verify that the correct amount of coins is sent to their output addresses.
“Mixing services (e.g., [22] or [70]) are anonymous service providers that divide users' funds into smaller parts; then, these parts are randomly mixed to make users and transactions unlinkable. Users can mix their coins to generate one mixing transaction based on the users' addresses, in such a way that users are still able to verify that the correct amount of coins is sent to their output address”
From Privacy-Preserving Solutions for Blockchain: Review and Challenges (2019) · cites this paper as [22]
Cites
Tor: The Second-Generation Onion Router
Dingledine, R., Mathewson, N., & Syverson, P. (2004) · doi:10.21236/ada465464 · Cited by 4,104 · see citing works
Zerocoin: Anonymous Distributed E-Cash from Bitcoin
Miers, I., Garman, C., Green, M., & Rubin, A. D. (2013) · 2013 IEEE Symposium on Security and Privacy · doi:10.1109/sp.2013.34 · Cited by 983 · see citing works
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An Overview of Blockchain Technology: Architecture, Consensus, and Future Trends
Zheng, Z., Xie, S., Dai, H., Chen, X., & Wang, H. (2017) · 2017 IEEE International Congress on Big Data (BigData Congress) · doi:10.1109/bigdatacongress.2017.85 · Cited by 4,515 · see citing works
Blockchain challenges and opportunities: a survey
Zheng, Z., Xie, S., Dai, H. N., Chen, X., & Wang, H. (2018) · International Journal of Web and Grid Services · doi:10.1504/ijwgs.2018.095647 · Cited by 3,651 · see citing works
On blockchain and its integration with IoT. Challenges and opportunities
Reyna, A., Martín, C., Chen, J., Soler, E., & Díaz, M. (2018) · Future Generation Computer Systems · doi:10.1016/j.future.2018.05.046 · Cited by 1,908 · see citing works
Bitcoin and beyond: a technical survey on decentralized digital currencies
Tschorsch, F., & Scheuermann, B. (2016) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2016.2535718 · Cited by 1,690 · see citing works
Nofer, M., Gomber, P., Hinz, O., & Schiereck, D. (2017) · Business & Information Systems Engineering · doi:10.1007/s12599-017-0467-3 · Cited by 1,212 · see citing works
A Survey on Security and Privacy Issues of Bitcoin
Conti, M., Sandeep Kumar, E., Lal, C., & Ruj, S. (2018) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2018.2842460 · Cited by 1,116 · see citing works
A Review on the Use of Blockchain for the Internet of Things
Fernandez-Carames, T. M., & Fraga-Lamas, P. (2018) · IEEE Access · doi:10.1109/access.2018.2842685 · Cited by 1,078 · see citing works
Hassan, M. U., Rehmani, M. H., & Chen, J. (2019) · Future Generation Computer Systems · doi:10.1016/j.future.2019.02.060 · Cited by 520 · see citing works
Privacy-Preserving Solutions for Blockchain: Review and Challenges
Bernal Bernabe, J., Canovas, J. L., Hernandez-Ramos, J. L., Torres Moreno, R., & Skarmeta, A. (2019) · IEEE Access · doi:10.1109/access.2019.2950872 · Cited by 430 · see citing works
“To cope with these challenges, some proposals for blockchain such as mixers services [22], [23] try to pro-”
BackgroundMethodSanka, A. I., Irfan, M., Huang, I., & Cheung, R. C. C. (2021) · Computer Communications · doi:10.1016/j.comcom.2020.12.028 · Cited by 265 · see citing works
Ali, M., Karimipour, H., & Tariq, M. (2021) · Computers & Security · doi:10.1016/j.cose.2021.102355 · Cited by 177 · see citing works
Security Aspects of Blockchain Technology Intended for Industrial Applications
Idrees, S. M., Nowostawski, M., Jameel, R., & Mourya, A. K. (2021) · Electronics · doi:10.3390/electronics10080951 · Cited by 127 · see citing works
An Integrated Reward and Reputation Mechanism for MCS Preserving Users’ Privacy
Tanas, C., Delgado-Segura, S., & Herrera-Joancomartí, J. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-29883-2_6 · Cited by 37 · see citing works
When the cookie meets the blockchain: Privacy risks of web payments via cryptocurrencies
Goldfeder, S., Kalodner, H., Reisman, D., & Narayanan, A. (2018) · Proceedings on Privacy Enhancing Technologies · doi:10.1515/popets-2018-0038 · Cited by 29 · see citing works
Self-citation
- Authors
- Bonneau, J., Narayanan, A., Miller, A., Clark, J., Kroll, J. A., & Felten, E. W.
- Affiliations
- Princeton University (US)
- University of Maryland, College Park (US)
- Concordia University (CA)
- Corresponding author
- Bonneau, Joseph
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2014
- Pages
- 486-504
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1589846406
- Cited by
- 441
- References
- 2
- Citations by year
- 2026: 13 · 2025: 19 · 2024: 23 · 2023: 39 · 2022: 41 · 2021: 74 · 2020: 56 · 2019: 64 · 2018: 44 · 2017: 23 · 2016: 19 · 2015: 20 · 2014: 6
- FWCI
- 19.34
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- Lecture notes in computer science (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Physical Sciences › Computer Science › Artificial Intelligence › Internet Traffic Analysis and Secure E-voting
- Physical Sciences › Computer Science › Artificial Intelligence › Cryptography and Data Security
- Keywords
- cryptocurrency anonymity, Bitcoin, incentive alignment, anonymity set, payment privacy
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