加密貨幣用戶詐欺行為使用馬可夫鏈模型 之 實證分 析： Bito交易所實證研究

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Title:	加密貨幣用戶詐欺行為使用馬可夫鏈模型之實證分析： Bito交易所實證研究 Empirical Analysis of Fraudulent Migration Behavior of Cryptocurrency Users Using Markov Chain Model: Empirical Study for Bito Exchange
Authors:	馮書瑜
Contributors:	財務金融學系
Keywords:	洗錢比特幣金融犯罪區塊鏈馬可夫鏈
Date:	2023
Issue Date:	2023-08-02 15:22:15 (UTC+8)
Abstract:	在加密貨幣日益受到市場投資者關注的情況下， Web3.0的到來對金融行業帶來了重大變革。然而，隨著技術的迅猛發展，也伴隨著各種新型犯罪手法的出現。投資人通常透過交易所參與加密貨幣市場，但由於對於加密貨幣的不了解導致詐騙案件層出不窮。許多新手投資者透過交易所進行加密貨幣的購買，由於相關觀念的不足，常常導致投資者遭受詐騙的危機，導致失去資金。因此，本研究旨在使用幣託交易所提供的正常和灰色樣本進行行為分析，並透過馬可夫鏈的方法來研究違法帳戶的行為。本研究將探討用戶的行為，並進行分析。將幣託交易所提供的正常和灰色樣本，以瞭解不同類型用戶的行為模式。透過分析用戶在交易所的行為模式並揭示出正常用戶和潛在違法用戶之間的差異。 This study focuses on the behavioral analysis of users on a cryp-tocurrency exchange using both normal and gray samples provided by the Bito exchange. By utilizing the Markov chain methodology, we aim to uncover patterns and discern discrepancies between regu-lar users and potential illicit users. This analysis is vital for gaining insights into the dynamics of the cryptocurrency market and effec-tively addressing the risks associated with fraudulent activities. Through our research, we aim to contribute to the development of strategies and measures to enhance security and protect users in the cryptocurrency ecosystem.
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