Balaskas, Anastasios, Franqueira, Virginia N. L. (2018) Analytical Tools for Blockchain: Review, Taxonomy and Open Challenges. In: 2018 International Conference on Cyber Security and Protection of Digital Services (Cyber Security). . pp. 1-8. IEEE ISBN 978-1-5386-4683-0. (doi:10.1109/cybersecpods.2018.8560672) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:77172)
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Official URL: https://doi.org/10.1109/cybersecpods.2018.8560672 |
Abstract
Bitcoin has introduced a new concept that could feasibly revolutionise the entire Internet as it exists, and positively impact on many types of industries including, but not limited to, banking, public sector and supply chain. This innovation is grounded on pseudo-anonymity and strives on its innovative decentralised architecture based on the blockchain technology. Blockchain is pushing forward a race of transaction-based applications with trust establishment without the need for a centralised authority, promoting accountability and transparency within the business process. However, a blockchain ledger (e.g., Bitcoin) tend to become very complex and specialised tools, collectively called “Blockchain Analytics”, are required to allow individuals, law enforcement agencies and service providers to search, explore and visualise it. Over the last years, several analytical tools have been developed with capabilities that allow, e.g., to map relationships, examine flow of transactions and filter crime instances as a way to enhance forensic investigations. This paper discusses the current state of blockchain analytical tools and presents a thematic taxonomy model based on their applications. It also examines open challenges for future development and research.
Item Type: | Conference or workshop item (Paper) |
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DOI/Identification number: | 10.1109/cybersecpods.2018.8560672 |
Uncontrolled keywords: | Blockchain; Cryptocurrency; Bitcoin; Tools; Blockchain Analytics; Digital Forensics; Cybercrime Investigation. |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing |
Depositing User: | Virginia Franqueira |
Date Deposited: | 16 Oct 2019 11:00 UTC |
Last Modified: | 04 Mar 2024 18:00 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/77172 (The current URI for this page, for reference purposes) |
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