運用馬可夫鏈模型分析加密貨幣用戶詐騙行為──以Bito交易所為例的實證研究

本文研究了Web3.0時代下，加密貨幣對金融行業的影響以及伴隨而來的新型犯罪挑戰。隨著技術進步，市場投資者對加密貨幣的興趣日增，但對於這一領域缺乏足夠認識的新手投資者，經常成為詐騙案件的受害者。許多人透過交易所購買加密貨幣，由於不熟悉加密貨幣的概念，面臨被詐騙的風險，導致資金損失。為此，本研究利用幣託交易所提供的正常與灰色帳戶數據，運用馬可夫鏈方法分析這些帳戶的行為模式，以辨識正常用戶與潛在違法用戶之間的行為差異。這項研究旨在透過用戶行為分析，提供對於違法帳戶行為的深入理解。

This paper investigates the impact of cryptocurrencies on the financial industry and the accompanying new criminal challenges in the era of Web3.0. As technology advances, market investors' interest in cryptocurrencies is growing, but novice investors, lacking sufficient understanding of this field, often fall victim to fraud cases. Many people purchase cryptocurrencies through exchanges and face the risk of being scammed due to unfamiliarity with cryptocurrency concepts, leading to financial losses. To address this, the study utilizes normal and grey account data provided by a cryptocurrency exchange and applies the Markov chain method to analyze the behavior patterns of these accounts. The aim is to identify the behavioral differences between regular users and potential illegal users. This research intends to provide a deeper understanding of illegal account behaviors through the analysis of user behavior.