BlockSci: Design and applications of a blockchain analysis platform


Harry Kalodner, Malte Möser, and Kevin Lee, Princeton University; Steven Goldfeder, Cornell Tech; Martin Plattner, University of Innsbruck; Alishah Chator, Johns Hopkins University; Arvind Narayanan, Princeton University


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.

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@inproceedings {255350,
author = {Harry Kalodner and Malte M{\"o}ser and Kevin Lee and Steven Goldfeder and Martin Plattner and Alishah Chator and Arvind Narayanan},
title = {{BlockSci}: Design and applications of a blockchain analysis platform},
booktitle = {29th USENIX Security Symposium (USENIX Security 20)},
year = {2020},
isbn = {978-1-939133-17-5},
pages = {2721--2738},
url = {},
publisher = {USENIX Association},
month = aug

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