Bitcoin csv dataset 2009-2019

  • Bitcoin blockchain dataset in raw form was obtained from VJTI Blockchain lab \footnote{https://www.vjti-bct.in/}.


  • The dataset was of size 298GB and consisted of Blockchain in the form of blk.data files. All blocks and transactions from 03 Jan 2009 12:45:05 GMT to 2019 were present in the dataset.


  • This raw data was then converted to CSV files using the blockchain parser built by the VJTI Blockchain lab \footnote{https://github.com/pranavn91/blockchain}.


  • The processed dataset, is made available for download


  • https://drive.google.com/file/d/1OrHGdhwY859u7yCW__UULIFTtjnTQsgL/view?usp=sharing


  • https://drive.google.com/file/d/11q7-Y8FCDxDXtJzkeBKsCxo21n2iepn8/view?usp=sharing


  • https://drive.google.com/file/d/1rOBfsQbAeJIygWqZSjPiEcYjXrGN3DN5/view?usp=sharing


  • https://drive.google.com/file/d/1Ksr7foIU-Ug2rV3jb8Wd8a3vDgSgt_a2/view?usp=sharing


  • dataset-300gb


    • Output -> tx_hash:ID and receiver_address and amount


  • Inputs -> sender_address and tx_hash:ID and amount


  • Transactions -> tx_hash:ID and timestamp


  • From the Transactions dataset, it is possible to obtain the count of transactions occurring in that year. Each transaction (tx) was identified in Blockchain by a unique hash (tx_hash:IDd ) and a timestamp, which was the UNIX time of the transaction.


  • Nerurkar, Pranav, et al. "Dissecting bitcoin blockchain: Empirical analysis of bitcoin network (2009–2020)." Journal of Network and Computer Applications 177 (2021): 102940.


  • Nerurkar, Pranav, Yann Busnel, Romaric Ludinard, Kunjal Shah, Sunil Bhirud, and Dhiren Patel. "Detecting illicit entities in bitcoin using supervised learning of ensemble decision trees." In Proceedings of the 2020 10th international conference on information communication and management, pp. 25-30. 2020.


  • Nerurkar, Pranav, Sunil Bhirud, Dhiren Patel, Romaric Ludinard, Yann Busnel, and Saru Kumari. "Supervised learning model for identifying illegal activities in Bitcoin." Applied Intelligence 51, no. 6 (2021): 3824-3843.