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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16081
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dc.contributor.authorBhatia, Ashutosh-
dc.contributor.authorTiwari, Kamlesh-
dc.date.accessioned2024-10-14T10:26:46Z-
dc.date.available2024-10-14T10:26:46Z-
dc.date.issued2022-03-
dc.identifier.urihttps://link.springer.com/chapter/10.1007/978-3-030-99584-3_40-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16081-
dc.description.abstractBitcoin is the first and most widely used cryptocurrency in the world. It provides a pseudonym identity to its users that is established using the user’s public key, which leads to preserving the user’s privacy. Each transfer of bitcoin cryptocurrency among the users makes a transaction. The pseudonym identities are considered as transaction end-points. These transactions are recorded on an immutable public ledger called Blockchain which is an append-only data structure. The popularity of Bitcoin has increased unreasonably. The general trend shows a positive response from the common masses indicating an increase in trust and privacy concerns which makes an interesting use case from the analysis point of view. Moreover, since the blockchain is publicly available and up-to-date, any analysis would provide a live insight into the usage patterns which ultimately would be useful for making a number of inferences by law-enforcement agencies, economists, tech-enthusiasts, etc. In this paper, we study various applications and techniques of performing data analytics over Bitcoin blockchain from a graph theoretic perspective. We also propose a framework for performing such data analytics and explored a couple of use cases using the proposed framework.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.subjectComputer Scienceen_US
dc.subjectBlockchainen_US
dc.subjectData Analyticsen_US
dc.subjectCryptocurrencyen_US
dc.titleBitcoin’s Blockchain Data Analytics: A Graph Theoretic Perspectiveen_US
dc.typeArticleen_US
Appears in Collections:Department of Computer Science and Information Systems

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