Volume 33, Issue 1 (IJIEPR 2022)                   IJIEPR 2022, 33(1): 162-175 | Back to browse issues page


XML Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Elhambakhsh F, Sabri-Laghaie K. The SCAN Method to Monitor Cryptocurrency Transactions. IJIEPR 2022; 33 (1) :162-175
URL: http://ijiepr.iust.ac.ir/article-1-1396-en.html
1- Iran University of Science and Technology
2- Urmia Univesity of Technology , sabri@uut.ac.ir
Abstract:   (1718 Views)
The fourth industrial revolution has changed our lives by enabling everyone to be interconnected virtually. A trustworthy system is required to secure large volume of stored data in IoT-based devices. Blockchain technology has led to transfer and to save data in a safe way. With this in mind, the blockchain-based cryptocurrencies have gained quite a bit of popularity because of their potential for financial transactions. In this regard, monitoring transactions network is very fruitful to find users’ abnormal behaviors. In this research, a novel procedure is used to monitor blockchain cryptocurrency transactions network. To do so, a random, binary graph model is used to simulate the transactions between users, and a SCAN method is used to detect the abnormal behaviors in the simulated model. Also, a multivariate exponentially weighted moving average (MEWMA) control chart is used to monitor centrality measures. The probability of signal is used to assess the performance of the SCAN method and that of the MEWMA control chart in distinguishing abnormalities. Then, the procedure is adopted to a Bitcoin transactions dataset.
Full-Text [PDF 719 kb]   (785 Downloads)    
Type of Study: Research | Subject: Statistical Process Control Statistical Process Control or Quality Control
Received: 2021/12/22 | Accepted: 2022/02/6 | Published: 2022/03/19

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.