publication . Preprint . 2017

BlockSci: Design and applications of a blockchain analysis platform

Kalodner, Harry; Goldfeder, Steven; Chator, Alishah; Möser, Malte; Narayanan, Arvind;
Open Access English
  • Published: 07 Sep 2017
Abstract
Analysis of blockchain data is useful for both scientific research and commercial applications. We present BlockSci, an open-source software platform for blockchain analysis. BlockSci is versatile in its support for different blockchains and analysis tasks. It incorporates an in-memory, analytical (rather than transactional) database, making it several hundred times faster than existing tools. We describe BlockSci's design and present four analyses that illustrate its capabilities. This is a working paper that accompanies the first public release of BlockSci, available at https://github.com/citp/BlockSci. We seek input from the community to further develop the s...
Subjects
free text keywords: Computer Science - Cryptography and Security, Computer Science - Databases
Funded by
NSF| TWC: Small: Addressing the challenges of cryptocurrencies: Security, anonymity, stability
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 1421689
  • Funding stream: Directorate for Computer & Information Science & Engineering | Division of Computer and Network Systems
,
NSF| Graduate Research Fellowship Program (GRFP)
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 1148900
  • Funding stream: Directorate for Education & Human Resources | Division of Graduate Education
Download from
16 references, page 1 of 2

[1] S. Goldfeder, H. Kalodner, D. Reisman, and A. Narayanan, “When the cookie meets the blockchain: Privacy risks of web payments via cryptocurrencies,” arXiv preprint arXiv:1708.04748, 2017. [OpenAIRE]

[2] A. Miller, M. Möser, K. Lee, and A. Narayanan, “An empirical analysis of linkability in the Monero blockchain,” arXiv preprint arXiv:1704.04299, 2017.

[3] M. Möser and R. Böhme, “The price of anonymity: empirical evidence from a market for Bitcoin anonymization,” Journal of Cybersecurity, 2017.

[4] --, “Trends, tips, tolls: A longitudinal study of Bitcoin transaction fees,” in vol. 8976. Springer, 2015, pp. 19-33.

[5] F. McSherry, M. Isard, and D. G. Murray, “Scalability! But at what COST?” in HotOS, 2015.

[6] R. Gennaro, S. Goldfeder, and A. Narayanan, “Threshold-optimal DSA/ECDSA signatures and an application to Bitcoin wallet security,” in International Conference on Applied Cryptography and Network Security. Springer, 2016, pp. 156-174. [OpenAIRE]

[7] S. Meiklejohn, M. Pomarole, G. Jordan, K. Levchenko, D. McCoy, G. M. Voelker, and S. Savage, “A stful of Bitcoins: characterizing payments among men with no names,” in Proceedings of the 2013 Internet Measurement Conference (IMC). ACM, 2013, pp. 127-140.

[8] W. Jakob, “Lock-free parallel disjoint set data structure,” https://github.com/ wjakob/dset, 2015.

[9] A. Y. Ng, M. I. Jordan, and Y. Weiss, “On spectral clustering: Analysis and an algorithm,” in Advances in neural information processing systems, 2002, pp. 849- 856.

[10] J. Rubin, “Bitcoin spark framework (btcspark),” https://github.com/JeremyRubin/ BTCSpark.

[11] znort987, “blockparser,” https://github.com/znort987/blockparser.

[12] M. Bartoletti, A. Bracciali, S. Lande, and L. Pompianu, “A general framework for Bitcoin analytics,” arXiv preprint arXiv:1707.01021, 2017. [OpenAIRE]

[13] “Shop with Dash,” https://www.dash.org/merchants/, 2017.

[14] dnaleor, “Warning: DASH privacy is worse than Bitcoin,” https://steemit.com/ bitcoin/@dnaleor/warning-dash-privacy-is-worse-than-bitcoin, 2016.

[15] N. ODell, “StackExchange: How often do miners update their block transaction list?” https://bitcoin.stackexchange.com/questions/32892/ how-often-do-miners-update-their-block-transaction-list, 2014.

16 references, page 1 of 2
Abstract
Analysis of blockchain data is useful for both scientific research and commercial applications. We present BlockSci, an open-source software platform for blockchain analysis. BlockSci is versatile in its support for different blockchains and analysis tasks. It incorporates an in-memory, analytical (rather than transactional) database, making it several hundred times faster than existing tools. We describe BlockSci's design and present four analyses that illustrate its capabilities. This is a working paper that accompanies the first public release of BlockSci, available at https://github.com/citp/BlockSci. We seek input from the community to further develop the s...
Subjects
free text keywords: Computer Science - Cryptography and Security, Computer Science - Databases
Funded by
NSF| TWC: Small: Addressing the challenges of cryptocurrencies: Security, anonymity, stability
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 1421689
  • Funding stream: Directorate for Computer & Information Science & Engineering | Division of Computer and Network Systems
,
NSF| Graduate Research Fellowship Program (GRFP)
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 1148900
  • Funding stream: Directorate for Education & Human Resources | Division of Graduate Education
Download from
16 references, page 1 of 2

[1] S. Goldfeder, H. Kalodner, D. Reisman, and A. Narayanan, “When the cookie meets the blockchain: Privacy risks of web payments via cryptocurrencies,” arXiv preprint arXiv:1708.04748, 2017. [OpenAIRE]

[2] A. Miller, M. Möser, K. Lee, and A. Narayanan, “An empirical analysis of linkability in the Monero blockchain,” arXiv preprint arXiv:1704.04299, 2017.

[3] M. Möser and R. Böhme, “The price of anonymity: empirical evidence from a market for Bitcoin anonymization,” Journal of Cybersecurity, 2017.

[4] --, “Trends, tips, tolls: A longitudinal study of Bitcoin transaction fees,” in vol. 8976. Springer, 2015, pp. 19-33.

[5] F. McSherry, M. Isard, and D. G. Murray, “Scalability! But at what COST?” in HotOS, 2015.

[6] R. Gennaro, S. Goldfeder, and A. Narayanan, “Threshold-optimal DSA/ECDSA signatures and an application to Bitcoin wallet security,” in International Conference on Applied Cryptography and Network Security. Springer, 2016, pp. 156-174. [OpenAIRE]

[7] S. Meiklejohn, M. Pomarole, G. Jordan, K. Levchenko, D. McCoy, G. M. Voelker, and S. Savage, “A stful of Bitcoins: characterizing payments among men with no names,” in Proceedings of the 2013 Internet Measurement Conference (IMC). ACM, 2013, pp. 127-140.

[8] W. Jakob, “Lock-free parallel disjoint set data structure,” https://github.com/ wjakob/dset, 2015.

[9] A. Y. Ng, M. I. Jordan, and Y. Weiss, “On spectral clustering: Analysis and an algorithm,” in Advances in neural information processing systems, 2002, pp. 849- 856.

[10] J. Rubin, “Bitcoin spark framework (btcspark),” https://github.com/JeremyRubin/ BTCSpark.

[11] znort987, “blockparser,” https://github.com/znort987/blockparser.

[12] M. Bartoletti, A. Bracciali, S. Lande, and L. Pompianu, “A general framework for Bitcoin analytics,” arXiv preprint arXiv:1707.01021, 2017. [OpenAIRE]

[13] “Shop with Dash,” https://www.dash.org/merchants/, 2017.

[14] dnaleor, “Warning: DASH privacy is worse than Bitcoin,” https://steemit.com/ bitcoin/@dnaleor/warning-dash-privacy-is-worse-than-bitcoin, 2016.

[15] N. ODell, “StackExchange: How often do miners update their block transaction list?” https://bitcoin.stackexchange.com/questions/32892/ how-often-do-miners-update-their-block-transaction-list, 2014.

16 references, page 1 of 2
Powered by OpenAIRE Research Graph
Any information missing or wrong?Report an Issue