| Title: | Synergy of blockchain technology and data mining techniques for anomaly detection |
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| Authors: | ID Kamišalić Latifić, Aida (Author)
ID Kovačević, Renata (Author)
ID Fister, Iztok (Author) |
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| Files: |  applsci-11-07987-v2.pdf (681,73 KB)
MD5: 41F43303EE64D671F37DD0D30E498D49
 https://www.mdpi.com/2076-3417/11/17/7987
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| Language: | English |
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| Work type: | Article |
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| Typology: | 1.02 - Review Article |
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| Organization: | FERI - Faculty of Electrical Engineering and Computer Science
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| Abstract: | Blockchain and Data Mining are not simply buzzwords, but rather concepts that are playing
an important role in the modern Information Technology (IT) revolution. Blockchain has recently
been popularized by the rise of cryptocurrencies, while data mining has already been present in IT
for many decades. Data stored in a blockchain can also be considered to be big data, whereas data
mining methods can be applied to extract knowledge hidden in the blockchain. In a nutshell, this
paper presents the interplay of these two research areas. In this paper, we surveyed approaches for
the data mining of blockchain data, yet show several real-world applications. Special attention was
paid to anomaly detection and fraud detection, which were identified as the most prolific applications
of applying data mining methods on blockchain data. The paper concludes with challenges for future
investigations of this research area. |
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| Keywords: | anomaly detection, blockchain, distributed ledger, data mining, machine learning |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 27.07.2021 |
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| Article acceptance date: | 25.08.2021 |
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| Publication date: | 29.08.2021 |
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| Publisher: | MDPI |
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| Year of publishing: | 2021 |
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| Number of pages: | 38 str. |
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| Numbering: | Vol. 11, no. 17 |
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| PID: | 20.500.12556/DKUM-93179  |
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| UDC: | 004.8 |
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| ISSN on article: | 2076-3417 |
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| COBISS.SI-ID: | 74447619 |
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| DOI: | 10.3390/app11177987 |
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| Copyright: | © 2021 by the authors |
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| Publication date in DKUM: | 16.06.2025 |
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| Views: | 147 |
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| Downloads: | 9 |
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| Metadata: |    |
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| Categories: | Misc.
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