• Journal of Digital Convergence
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• v.16 no.9
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• pp.133-145
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• 2018

This study was investigated the necessity and possibility of using block-chain technology in online used-goods trading platform. Current online used-goods trading platforms operate a safety trading system, but it is difficult to utilize due to relatively high commission rate. As a result, people mainly use the method of meeting and purchasing in person, which is a relatively costly method. This study discusses how to build a platform to solve or mitigate problems such as privacy, information distortion and omission, fraud, etc. In the platform proposed in this study, it is possible to solve the major fraud and personal information protection problems that may occur in the transaction proceeding by appropriately reflecting the types and characteristics of the block-chain technology. In future work, we will discuss legal framework and technology development plan to apply the proposed platform in this study.

• Journal of Internet of Things and Convergence
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• v.5 no.2
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• pp.81-87
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• 2019

It is changing to the 4^th Industrial Revolution rapidly as the information age through the Internet is changing, and it is rapidly changing to the era of the IoT using all things. In education, with the change to the Internet of Things, interest in education for the 4th Industrial Revolution is increasing. It is necessary to change from NetPBL method using Internet to T-PBL using Triz. In this paper, we focus on the task-based learning (T-PBL) method using Triz and examine the necessity and importance of its use. We propose a teaching model using Triz as a tool for T-PBL. Triz is being used as a tool to solve problems in creative ways. We will design a model applying Triz to the blockchain system security class related to the IoT.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.5
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• pp.11-19
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• 2021

In this paper, we proposed an asymmetric multi-core processor scheduling scheme which is based on the mileage of each core. We considered a big-LITTLE multi-core processor structure, which consists of low power consuming LITTLE cores with general performance and high power consuming big cores with high performance. If a task needs to be processed, the processor decides a core type (big or LITTLE) to handle the task, and then investigate the core with the shortest mileage among unoccupied cores. Then assigns the task to the core. We developed a mileage-based balancing algorithm for asymmetric multi-core assignment and showed that the proposed scheduling scheme is more cost-effective compared to the traditional scheme from a management perspective. Simulation is also conducted for the purpose of performance evaluation of our proposed algorithm.

• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.600-607
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• 2021

Purpose: The purpose of this study is to examine the path of money laundering of criminal proceeds through cryptocurrency using criminal script analysis and to devise measures to prevent and prevent criminal justice agencies from doing so. Method: Based on the results of a prior study on the profit path of cryptocurrency through money laundering and criminal cases in Korea, the path of money laundering was analyzed using criminal script techniques. Result: Most of the cryptocurrencies that have been launched are converted into criminal proceeds, which are re-launched and cashed or have a vicious cycle of being used as criminal funds are used. According to the script, the route of money laundering is mainly converted to criminal proceeds from cryptocurrency exchanges using anonymity, which is repeated several times, making it very difficult to find the money using cryptocurrency in criminal justice institutions. Conclusion: As the method of money laundering using cryptocurrency is becoming more sophisticated, legal sanctions and preventive institutionalization should be prepared for the prohibition or confiscation of cryptocurrency transactions for money laundering after understanding the flow.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.4
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• pp.637-659
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• 2021

Since the creation of the first Bitcoin blockchain in 2009, the number of cryptocurrency users has steadily increased. However, the number of hacking attacks targeting assets stored in these users' cryptocurrency wallets is also increasing. Therefore, we evaluate the security of the wallets currently on the market to ensure that they are safe. We first conduct threat modeling to identify threats to cryptocurrency wallets and identify the security requirements. Second, based on the derived security requirements, we utilize attack trees and Bayesian network analysis to quantitatively measure the risks inherent in each wallet and compare them. According to the results, the average total risk in software wallets is 1.22 times greater than that in hardware wallets. In the comparison of different hardware wallets, we found that the total risk inherent to the Trezor One wallet, which has a general-purpose MCU, is 1.11 times greater than that of the Ledger Nano S wallet, which has a secure element. However, use of a secure element in a cryptocurrency wallet has been shown to be less effective at reducing risks.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1287-1295
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• 2021

During the past decade, it seems apparent that Bitcoin has been the best performing asset class. Even without a centralized authority that takes control over, Bitcoin, which started off with basically no value at all, reached around 65000 dollars in 2021, showing a movement that will definitely go down in history. Thus, even those who were skeptical of Bitcoin's intangible nature are stacking bitcoin as a huge part of their portfolios. Bitcoin's exponential growth in value also caught the attention of traditional banking and investment firms. Along with the spotlight Bitcoin is getting from the investment world, research using macro-economic variables and investor sentiment to explain Bitcoin's price movement has shown progress. However, previous studies do not make use of On-Chain Data, which are data processed using transaction data in Bitcoin's blockchain network. Therefore, in this paper, we will be utilizing LSTM, a method widely used for time-series data prediction, with On-Chain Data to predict the price of Bitcoin.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1067-1078
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• 2020

With the development of internet technology, a lot of content is produced, and the demand for it is increasing. Accordingly, the number of contents in circulation is increasing, while the number of distributing illegal copies that infringe on copyright is also increasing. The Korea Copyright Protection Agency operates a illegal content obstruction program based on substring matching, and it is difficult to accurately search because a large number of noises are inserted to bypass this. Recently, researches using natural language processing and AI deep learning technologies to remove noise and various blockchain technologies for copyright protection are being studied, but there are limitations. In this paper, noise is removed from data collected online, and keyword-based illegal copies are searched. In addition, the same heavy uploader is estimated through profiling analysis for heavy uploaders. In the future, it is expected that copyright damage will be minimized if the illegal copy search technology and blocking and response technology are combined based on the results of profiling analysis for heavy uploaders.

• Journal of Information Technology Services
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• v.19 no.6
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• pp.131-144
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• 2020

As the blockchain technology attracts attention, interest in cryptocurrency that is received as a reward is also increasing. Currently, investments and transactions are continuing with the expectation and increasing value of cryptocurrency. Accordingly, prediction for cryptocurrency price has been attempted through artificial intelligence technology and social sentiment analysis. The purpose of this paper is to develop a deep learning ensemble model for predicting the price fluctuations and one-day lag price of cryptocurrency based on the design science research method. This paper intends to perform predictive modeling on Ethereum among cryptocurrencies to make predictions more efficiently and accurately than existing models. Therefore, it collects data for five years related to Ethereum price and performs pre-processing through customized functions. In the model development stage, four LSTM models, which are efficient for time series data processing, are utilized to build an ensemble model with the optimal combination of hyperparameters found in the experimental process. Then, based on the performance evaluation scale, the superiority of the model is evaluated through comparison with other deep learning models. The results of this paper have a practical contribution that can be used as a model that shows high performance and predictive rate for cryptocurrency price prediction and price fluctuations. Besides, it shows academic contribution in that it improves the quality of research by following scientific design research procedures that solve scientific problems and create and evaluate new and innovative products in the field of information systems.

• The Journal of Information Systems
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• v.30 no.4
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• pp.119-152
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• 2021

The concept of Self-Sovereign Identity (SSI) has emerged to overcome the limitations of traditional centralized personal identity management systems in our society. Therefore, in this study, 36 seminal researches out of 112 collected studies were investigated with a systematic literature review method to deliver a core common definition as well as the research trends on SSI in the socioeconomic, legal and technological fields. SSI studies in the legal field have mainly considered the conflicts with relevant laws such as General Data Protection Regulation (GDPR) and privacy protection laws. The study of SSI in the technology field have looked at the trends of the technical components to implement SSI and discussed the necessities of establishing standards to increase interoperability for SSI diffusion worldwide. This study ultimately derived the core definition of SSI from a various academic fields as "a trust-based personal identity management system that enables autonomous self-identification by a identity owner without a centralized system or 3rd party intervention". The results of this study contribute to the understanding of the essential SSI concept which were varied on different research fields and industries. The results also provide a foundation for discovering various SSI-based business models, applications as well as future research opportunities. Furthermore, this study suggested that SSI must be developed with interdisciplinary manner among the socioeconomic, legal, and technological fields to be practically applicable system to enable autonomous self-identification by a identity owner in our society.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.47-53
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• 2023

In this paper, based on the generalization and popularization of NFT, the utilization idea of using NFT in e-sports was proposed. We considered ways to utilize NFTs to make access to e-sports easy for all users and to secure users from various age groups. To this end, cases of NFTs with diversity in e-sports platforms were analyzed by type, and the degree of use of NFTs in e-sports was identified through a survey. As a result of the study, it was found that the NFT experience in the e-sports game was highly satisfactory and the desire to experience it again was strong. As NFTs have ownership and scarcity as important characteristics, they can respond well to the demand for owning unique items in e-sports. In addition, in marketing, by promoting limited edition products with scarcity, it is possible to promote marketing that creates value with high profitability. When using NFT in e-sports, various NFT functions are combined regardless of the type of sport, so NFT can become an economic infrastructure.