• The Journal of the Korea Contents Association
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• v.19 no.8
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• pp.194-204
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• 2019

This study aims to review previous research on the key elements of an Initial Coin Offering (ICO) and establish their priorities in order to help relevant stakeholders build and invigorate an ecosystem that integrates blockchain technology with the digital content industry. To achieve this goal, we first structured the key elements identified from previous studies into a hierarchy model. We then assigned weighted values to each element using the Analytic Hierarchy Process (AHP) methodology. Among the main elements, the priorities were identified as follows, from most important to least: Business (0.422) > Technology (0.172) > Contents (0.144) > Human Resources (0.104) > Institutions (0.099) > Token (0.059). With regard to the sub-elements, the weighted values were found to be as follows, in descending order: Probability (0.162) > Laws and Regulations (0.071) > Estimated Growth (0.063). The implications of the results are also described within the present study. The findings of this study will be of great value to ICO founders as well as investors and provide a much-needed academic basis for the burgeoning blockchain-integrated ecosystems and businesses.

• Smart Media Journal
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• v.11 no.5
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• pp.63-74
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• 2022

Initial public offering (IPO) has a legal framework for investor protection, and because there are various quantitative evaluation factors, objective analysis is possible, and various studies have been conducted. In addition, crowdfunding also has several devices to prevent indiscriminate funding as the legal system for investor protection. On the other hand, the blockchain-based cryptocurrency white paper (ICO), which has recently been in the spotlight, has ambiguous legal means and standards to protect investors and lacks quantitative evaluation methods to evaluate ICOs objectively. Therefore, this study collects online-published ICO white papers to detect fraud in ICOs, performs ICO fraud predictions based on BERT, a text embedding technique, and compares them with existing Random Forest machine learning techniques, and shows the possibility on fraud detection. Finally, this study is expected to contribute to the study of ICO fraud detection based on quantitative methods by presenting the possibility of using a quantitative approach using unstructured data to identify frauds in ICOs.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.409-411
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• 2019

최근 ICO(Initial Coin Offering)를 악용한 투자 피해 사례가 계속해서 보고되고 있다. 이처럼 ICO 의 문제점이 드러나면서 ICO 의 장점을 그대로 가지면서도 법의 규제 하에서 투자자를 보호할 수 있는 STO(Security Token Offering)에 대한 관심이 높아지고 있다. 본 논문에서는 STO 에 대해 연구하고 국내 시장에서의 STO 의 확산 및 법제화를 촉구한다.