نشریه بین المللی مهندسی صنایع و تحقیقات تولید

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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.

     

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