Abstract
Bitcoin is the most successful cryptocurrency since its inception in 2009 [30]. There are 18.1 million BTCs in circulation as of December 2019, which roughly translates to 149 Billion USD [12]. With Bitcoin’s substantial market capitalization and unique features like pseudo-anonymity and immutability, it draws much attention from the researchers across the world. Despite this enormous spotlight towards Bitcoin, it remains under-researched because of the large size of the Bitcoin Data, (Roughly 250 GB) and the inability to process this data in small time. To explore avenues for further research, this article presents a survey of the recent advancements done regarding the big data analytics of the Bitcoin Cryptocurrency. Furthermore, we propose an analysis framework based on the Apache Hadoop ecosystem.
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Complete Address: 1DkyBEKt5S2GDtv7aQw6rQepAvnsRyHoYM.
References
AntPool: Mining pools. https://v3.antpool.com/home
Apache: Apache hadoop. https://hadoop.apache.org/
Narayanan, A., Bonneau, J., Felten, E., Miller, A., Goldfeder, S.: Bitcoin and Cryptocurrency Technologies—A Comprehensive Introduction. Princeton Press, Princeton (2016)
Bag, S., Ruj, S., Sakurai, K.: Bitcoin block withholding attack: analysis and mitigation. IEEE Trans. Inf. Forensics Secur. 12(8), 1967–1978 (2017). https://doi.org/10.1109/TIFS.2016.2623588
Berrang, P., von Styp-Rekowsky, P., Wissfeld, M., França, B., Trinkler, R.: Albatross – an optimistic consensus algorithm. In: 2019 Crypto Valley Conference on Blockchain Technology (CVCBT), pp. 39–42 (2019). https://doi.org/10.1109/CVCBT.2019.000-1
BitLaundry. http://app.bitlaundry.com/
Blockchain.info. https://blockchain.info/q/
Brugere, I.: Bitcoin-transaction-network-extraction. https://github.com/ivanbrugere/Bitcoin-Transaction-Network-Extraction
BTC.com: Mining pools. https://btc.com/
C-hound. https://www.c-hound.ai/
Coinbase: Coinbase-wallet. https://wallet.coinbase.com/
Coindesk: Bitcoin(USD) price. http://www.coindesk.com/price/
Bitcoin core. https://bitcoin.org/en/bitcoin-core/
Domingues, P., Frade, M., Parreira, J.: Filtering email addresses, credit card numbers and searching for bitcoin artifacts with the autopsy digital forensics software, pp. 318–328 (2020). https://doi.org/10.1007/978-3-030-17065-3_32
Bitcoin fog. http://www.bitcoinfog.info/
Gear, M.: Start accepting bitcoin payments. https://gear.mycelium.com
Gennaro, R., Jarecki, S., Krawczyk, H., Rabin, T.: Secure distributed key generation for discrete-log based cryptosystems. J. Cryptol. 20(1), 51–83 (2007). https://doi.org/10.1007/s00145-006-0347-3
Giaglis, G., Georgoula, I., Pournarakis, D., Bilanakos, C., Sotiropoulos, D.: Using time-series and sentiment analysis to detect the determinants of bitcoin prices (2015). https://doi.org/10.2139/ssrn.2607167
Harrigan, M., Fretter, C.: The unreasonable effectiveness of address clustering. In: 2016 International IEEE Conferences on Ubiquitous Intelligence Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld), pp. 368–373 (2016). https://doi.org/10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0071
Harrigan, M., Shi, L., Illum, J.: Airdrops and privacy: a case study in cross-blockchain analysis. In: 2018 IEEE International Conference on Data Mining Workshops (ICDMW), pp. 63–70 (2018). https://doi.org/10.1109/ICDMW.2018.00017
Haslhofer, B., Karl, R., Filtz, E.: O bitcoin where art thou? Insight into large-scale transaction graphs. In: SEMANTiCS (Posters, Demos) (2016)
Isenberg, P., Kinkeldey, C., Fekete, J.-D.: Exploring entity behavior on the bitcoin blockchain. In: Posters of the IEEE Conference on Visualization (2017)
Jang, H., Lee, J.: An empirical study on modeling and prediction of bitcoin prices with Bayesian neural networks based on blockchain information. IEEE Access PP, 1 (2017). https://doi.org/10.1109/ACCESS.2017.2779181
Kalodner, H., Goldfeder, S., Chator, A., Möser, M., Narayanan, A.: Blocksci: Design and applications of a blockchain analysis platform (2017)
Kaushal, P.K., Bagga, A., Sobti, R.: Evolution of bitcoin and security risk in bitcoin wallets. In: 2017 International Conference on Computer, Communications and Electronics (Comptelix), pp. 172–177 (2017). https://doi.org/10.1109/COMPTELIX.2017.8003959
Liu, Y., Li, R., Liu, X., Wang, J., Tang, C., Kang, H.: Enhancing anonymity of bitcoin based on ring signature algorithm. In: 2017 13th International Conference on Computational Intelligence and Security (CIS), pp. 317–321 (2017). https://doi.org/10.1109/CIS.2017.00075
McGinn, D., Birch, D., Akroyd, D., Molina-Solana, M., Guo, Y., Knottenbelt, W.: Visualizing dynamic bitcoin transaction patterns. Big Data 4, 109–119 (2016). https://doi.org/10.1089/big.2015.0056
Meiklejohn, S., Pomarole, M., Jordan, G., Levchenko, K., Mccoy, D., Voelker, G., Savage, S.: A fistful of bitcoins: Characterizing payments among men with no names. Commun. ACM 59, 86–93 (2016)
Möser, M., Böhme, R., Breuker, D.: An inquiry into money laundering tools in the bitcoin ecosystem. In: 2013 APWG eCrime Researchers Summit, pp. 1–14 (2013). https://doi.org/10.1109/eCRS.2013.6805780
Nakamoto, S., et al.: Bitcoin: A peer-to-Peer Electronic Cash System (2008)
O’Dwyer, K.J., Malone, D.: Bitcoin mining and its energy footprint. In: 25th IET Irish Signals Systems Conference 2014 and 2014 China-Ireland International Conference on Information and Communications Technologies (ISSC 2014/CIICT 2014), pp. 280–285 (2014). https://doi.org/10.1049/cp.2014.0699
OnionBC. http://6fgd4togcynxyclb.onion/
Chain-analysis reactor. https://www.chainalysis.com/
Reid, F., Harrigan, M.: An analysis of anonymity in the bitcoin system. In: 2011 IEEE Third International Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third International Conference on Social Computing, pp. 1318–1326 (2011). https://doi.org/10.1109/PASSAT/SocialCom.2011.79
Sahoo, M.S., Baruah, P.K.: Hbasechaindb - a scalable blockchain framework on hadoop ecosystem. In: Yokota, R., Wu, W. (eds.) Supercomputing Frontiers, pp. 18–29. Springer International Publishing, Cham (2018)
Shah, D., Zhang, K.: Bayesian regression and bitcoin. In: 2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014 (2014). https://doi.org/10.1109/ALLERTON.2014.7028484
Slush: Mining pools. https://slushpool.com/home/
Sun, Y., Xiong, H., Yiu, S.M., Lam, K.Y.: Bitvis: An interactive visualization system for bitcoin accounts analysis. In: 2019 Crypto Valley Conference on Blockchain Technology (CVCBT), pp. 21–25 (2019). https://doi.org/10.1109/CVCBT.2019.000-3
Van Der Horst, L., Choo, K.R., Le-Khac, N.: Process memory investigation of the bitcoin clients electrum and bitcoin core. IEEE Access 5, 22385–22398 (2017). https://doi.org/10.1109/ACCESS.2017.2759766
WalletExplorer: smart bitcoin block explorer. http://www.WalletExplorer.com
Wang, Q., Li, X., Yu, Y.: Anonymity for bitcoin from secure escrow address. IEEE Access 6, 12336–12341 (2018). https://doi.org/10.1109/ACCESS.2017.2787563
Wikipedia: Address reuse. https://en.bitcoin.it/wiki/Address_reuse
Wood, G.: Ethereum: a secure decentralised generalised transaction ledger. Ethereum Proj. Yellow Pap. 151, 1–32 (2014)
Xiao, R., Ren, W., Zhu, T., Choo, K.R.: A mixing scheme using a decentralized signature protocol for privacy protection in bitcoin blockchain. IEEE Trans. Dependable Secure Comput. 1 (2019). https://doi.org/10.1109/TDSC.2019.2938953
Huang, Y., Hirshman, Y., Macke, S.: Unsupervised approaches to detecting anomalous behavior in the bitcoin transaction network. URL https://pdfs.semanticscholar.org/2ea6/04d967ca11ec869545ace248c41db6a49855.pdf
Yue, X., Shu, X., Zhu, X., Du, X., Yu, Z., Papadopoulos, D., Liu, S.: Bitextract Interactive visualization for extracting bitcoin exchange intelligence. IEEE Trans. Visual Comput. Graphics PP, 1 (2018). https://doi.org/10.1109/TVCG.2018.2864814
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Shah, R.S., Bhatia, A. (2020). Bitcoin Data Analytics: Exploring Research Avenues and Implementing a Hadoop-Based Analytics Framework. In: Barolli, L., Amato, F., Moscato, F., Enokido, T., Takizawa, M. (eds) Web, Artificial Intelligence and Network Applications. WAINA 2020. Advances in Intelligent Systems and Computing, vol 1150. Springer, Cham. https://doi.org/10.1007/978-3-030-44038-1_17
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