• Journal of Platform Technology
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• v.8 no.4
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• pp.29-37
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• 2020

We propose a plan to reduce the operational risk of domestic cryptocurrency exchanges for protecting cryptocurrency exchange users and establishing a stable operating environment. For market participants using cryptocurrency exchanges, cryptocurrency exchange risk is greater than the price risk. In the cryptocurrency market, illegal transactions using the anonymity of cryptocurrency are occurring frequently. In addition, loss accidents due to cybercrimes and insider corruptions are continuing. And the resulting losses are passed on to the users of the exchange. In terms of operational risk, we analyze the current situation of domestic cryptocurrency exchanges and present the direction of development of each exchange platform to attract and protect users.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.583-590
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• 2022

With the release of the Bitcoin source in 2009, cryptocurrencies are continuously developing and expanding the market. Recently, new applicability is expanding centered on NFT coin and metaverse payment service. In particular, the Central Cryptocurrency Exchange actively supports relay transactions between cryptocurrencies or between traditional fiat currencies and cryptocurrencies. The cryptocurrency trading market based on such a central exchange encouraged speculative factors of cryptocurrencies, strongly arousing speculation and futility of cryptocurrencies. In addition, the central cryptocurrency exchange induces the centralization of users and virtual assets, thereby hindering the decentralization and security enhancement strategies of the block chain. Therefore, this study describes the current status and problems of centrally controlled centralized cryptocurrency exchanges in service, and presents a distributed cryptocurrency exchange modeling strategy and major issues as a decentralization model of the exchange. This research can strengthen the anonymity, decentralization, and autonomy of cryptocurrency based on blockchain.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.6
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• pp.113-123
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• 2018

There are no studies related to the cryptocurrency exchange, unlike the explosive topic and the active transaction of the cryptourrency around the world. In this study, variables were constructed based on the previous researches to examine the effects of e-service qualities(information quality, transaction quality, design quality, safety quality), satisfaction and continuance intention of cryptocurrency exchange. The samples consist of 180 survey data drawn from the users of cryptocurrency exchange. The collected data were analyzed by SPSS 24.0 and AMOS 21.0. According to results of the reliability and validity test, all were found reliable, and all items were included. As a result of hypothesis testing through path analysis, First, the e-service qualities (information quality, transaction quality, design quality, safety quality) of the cryptocurrency exchange showed positive effects on satisfaction at the significance level of 1% and 5%. Second, e-service qualities (information quality, transaction quality, design quality, safety quality) of the cryptocurrency exchange were found to have positive effects on continuance intention at the significance level of 1% and 5%. Third, the satisfaction of the cryptocurrency exchange has a positive effect on continuance intention at 1% level of significance.

• Journal of the Korea Convergence Society
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• v.10 no.10
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• pp.1-6
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• 2019

As the value of technical information increases, hacking attacks are trying to steal technical information through hacking. Recently, hacking of cryptocurrency exchanges is much easier to monetize than existing technical information, making it a major attack target for hackers. In the case of technical information, it is required to seize the technical information and sell it to the black market for cashing.In the case of cryptocurrency, most hacking attacks are concentrated on cryptocurrency exchanges because it is easy to cash out and not easy to track when successful hacking. Although technology cannot be hacked, cryptocurrency transactions traded on cryptocurrency exchanges are not recorded on the blockchain which is simply internal exchanges, so insiders may manipulate the quotes and leave gaps or leak out. Therefore, this research analyzes the recent hacking attacks of cryptocurrency exchanges and proposes solutions to secure cryptocurrency trading.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.7-12
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• 2024

To trade cryptocurrency, traders require a personal cryptocurrency wallet. Cryptocurrency itself using blockchain technology is guaranteed excellent security and reliability, so the threat of blockchain hacking is almost impossible, but the exchange environment used by traders for transactions is most subject to hacking threats. Even if transactions are made safely through blockchain during the transaction process, if the trader's wallet information itself is hacked, security cannot be secured in these processes. Exchange hacking is mainly done by stealing a trader's wallet information, giving the hacker access to the victim's wallet assets. In this paper, to prevent this, we would like to reconstruct the existing Hyperledger Fabric structure and propose a system that verifies the identity integrity of traders during the transaction process using whitelisting. The advantage is that through this process, damage to cryptocurrency assets caused by hackers can be prevented and recognized. In addition, we aim to point out and correct problems in the transaction process that may occur if the victim's wallet information is stolen from the existing Hyperledger Fabric.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.1
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• pp.187-194
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• 2019

Ever since the world's largest Bitcoin Echange, (Mt. Gox), was closed in March 2014 due to the series of hacking, still many other Exchages incl. recent Coinale in Korea have been attacked. Those hacking attempts never stopped and have caused significant threats to the overall industry of Crypto Currency and resulted in the loss of individual investors' asset. The DEX (Decentralized Exchange) has been proposed as a solution to fix the security problem at the Exchange, but still it is far away to resolve all issues. Therefore, this paper firstly analyzes security threats against existing Crypto Currency Exchanges and secondly derives security requirements for them. To do that it proposes a secure and distributed Crypto Currency Transaction Model through Personal Security devices as a solution. The paper also proves this new attempt by demonstrating its unique modelling; ultimately by adopting this modeling into Crypto Exchange is to avoid potential security threats.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.377-396
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• 2023

As the cryptocurrency market continues to grow, it has developed into a new financial market. The need for investment strategy research on the cryptocurrency market is also emerging. This study aims to conduct an empirical analysis on an investment methodology of cryptocurrency that combines short-term trading strategy and deep learning. Daily price data of the Ethereum was collected through the API of Upbit, the Korean cryptocurrency exchange. The investment performance of the experimental model was analyzed by finding the optimal parameters based on past data. The experimental model is a volatility breakout strategy(VBS), a Long Short Term Memory(LSTM) model, moving average cross strategy and a combined model. VBS is a short-term trading strategy that buys when volatility rises significantly on a daily basis and sells at the closing price of the day. LSTM is suitable for time series data among deep learning models, and the predicted closing price obtained through the prediction model was applied to the simple trading rule. The moving average cross strategy determines whether to buy or sell when the moving average crosses. The combined model is a trading rule made by using derived variables of the VBS and LSTM model using AND/OR for the buy conditions. The result shows that combined model is better investment performance than the single model. This study has academic significance in that it goes beyond simple deep learning-based cryptocurrency price prediction and improves investment performance by combining deep learning and short-term trading strategies, and has practical significance in that it shows the applicability in actual investment.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.52-57
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• 2022

In this study, keywords from representative online portal sites such as Naver, Google, and Youtube were collected based on text mining analysis technique using Textom to check the changes in metqaverse after COVID-19. before Corona, it was confirmed that social media platforms such as Kakao Talk, Facebook, and Twitter were mentioned, and among the four metaverse, consumer awareness was still concentrated in the field of life logging. However, after Corona, keywords from Roblox, Fortnite, and Geppetto appeared, and keywords such as Universe, Space, Meta, and the world appeared, so Metaverse was recognized as a virtual world. As a result, it was confirmed that consumer perception changed from the life logging of Metaverse to the mirror world. Third, keywords such as cryptocurrency, cryptocurrency, coin, and exchange appeared before Corona, and the word frequency ranking for blockchain, which is an underlying technology, was high, but after Corona, the word frequency ranking fell significantly as mentioned above.

• Journal of Information Technology Applications and Management
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• v.29 no.2
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• pp.17-25
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• 2022

Although the two types of currencies compete, the possibility of a virtual currency price bubble is diagnosed by assuming an economic model with currencies (won, virtual currency) that are intrinsically worthless. The won is supplied by the central bank to achieve the price stability target, while the supply of virtual currency increases by a fixed number. According to the basic price theory equation, as a simple proposition, cryptocurrency prices form a Martin Gale process [Schilling and Uhlig, 2019, p.20]. Based on the existing theoretical proposition, we applied the variance ratio verification method [Linton and Smetanina, 2016] and a simple technical chart method for empirical analysis. For the purpose of this study, the possibility of a bubble was empirically analyzed by analyzing the price volatility formed in the Korean virtual currency market over the past year, and brief policy implications for this were presented.

• Journal of the Korea Convergence Society
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• v.12 no.4
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• pp.249-258
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• 2021

Bitcoin prices have been soaring recently as investors flock to cryptocurrency exchanges. The purpose of this study is to predict the Bitcoin price using a deep learning model and analyze whether Bitcoin is profitable through investment strategy. LSTM is utilized as Bitcoin prediction model with nonlinearity and long-term memory and the profitability of MA cross-over strategy with predicted prices as input variables is analyzed. Investment performance of Bitcoin strategy using LSTM forecast prices from 2013 to 2021 showed return improvement of 5.5% and 46% more than market price MA cross-over strategy and benchmark Buy & Hold strategy, respectively. The results of this study, which expanded to recent data, supported the inefficiency of the cryptocurrency market, as did previous studies, and showed the feasibility of using the deep learning model for Bitcoin investors. In future research, it is necessary to develop optimal prediction models and improve the profitability of Bitcoin investment strategies through performance comparison of various deep learning models.