TY - GEN
T1 - BlockSci
T2 - 29th USENIX Security Symposium
AU - Kalodner, Harry
AU - Möser, Malte
AU - Lee, Kevin
AU - Goldfeder, Steven
AU - Plattner, Martin
AU - Chator, Alishah
AU - Narayanan, Arvind
N1 - Funding Information:
We are grateful to Lucas Mayer for prototype code, Danny Yuxing Huang, Pranay Anchuri, Shaanan Cohney, Rainer Böhme, Michael Fröwis, Jakob Hollenstein, Jason Anastasopoulos, Sarah Meiklejohn, and Dillon Reisman for useful discussions, and Chainalysis for providing access to their Reactor tool. We also thank the anonymous USENIX Security reviewers, the reviewers of the artifact evaluation process and our shepherd Anita Nikolich for their feedback. This work is supported by NSF grants CNS-1421689 and CNS-1651938, a grant from the Ripple University Blockchain Research Initiative, the European Union's Horizon 2020 research and innovation programme under grant agreement No. 740558, the Austrian FFG's KIRAS programme under project VIRTCRIME, and an NSF Graduate Research Fellowship under grant number DGE-1148900.
Funding Information:
This work is supported by NSF grants CNS-1421689 and CNS-1651938, a grant from the Ripple University Blockchain Research Initiative, the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 740558, the Austrian FFG’s KIRAS programme under project VIRTCRIME, and an NSF Graduate Research Fellowship under grant number DGE-1148900.
Publisher Copyright:
© 2020 by The USENIX Association. All Rights Reserved.
PY - 2020
Y1 - 2020
N2 - 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 orders of magnitudes faster than using general-purpose graph databases. We describe BlockSci's design and present four analyses that illustrate its capabilities, shedding light on the security, privacy, and economics of cryptocurrencies.
AB - 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 orders of magnitudes faster than using general-purpose graph databases. We describe BlockSci's design and present four analyses that illustrate its capabilities, shedding light on the security, privacy, and economics of cryptocurrencies.
UR - http://www.scopus.com/inward/record.url?scp=85091936517&partnerID=8YFLogxK
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M3 - Conference contribution
AN - SCOPUS:85091936517
T3 - Proceedings of the 29th USENIX Security Symposium
SP - 2721
EP - 2738
BT - Proceedings of the 29th USENIX Security Symposium
PB - USENIX Association
Y2 - 12 August 2020 through 14 August 2020
ER -