Information Systems Review (경영정보학연구)

The Korea Society of Management Information Systems (한국경영정보학회)
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A Study on Uncle Block Analysis of Blockchain Using Machine Learning Techniques

머신러닝 기법을 활용한 블록체인의 엉클블록 분석 연구

  • Han-Min Kim (Business School, Sungkyunkwan University)
  • 김한민 (성균관대학교 경영대학)
  • Received : 2019.05.13
  • Accepted : 2019.09.24
  • Published : 2020.02.29
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Abstract

Blockchain is emerging as a technology that can build trust between users participating in the system. As interest of Blockchain has increased, previous studies have mainly focused on cryptocurrency and application methods related to Blockchain technology. On the other hand, the studies on the stable implementation of Blockchain were rarely conducted. Typically, uncle block in the Blockchain plays an important role in the stable implementation of the Blockhain system, but no study was conducted on this. Drawing on this recognition, this study attempts to predict the uncle block of Blockchain using machine learning method, Blockchain information, and macro-economic factors. The results of artificial neural network and support vector machine analysis, Blockchain information and macro-economic factors contributed to the prediction of uncle block of Blockchain. In addition, artificial neural network using only Blockchain information provided the best performance for predicting the occurrence of uncle block. This study suggests ways to lead and contribute to Blockchain research in information systems filed.

블록체인은 시스템에 참여하는 사용자들 사이에 믿음을 확보할 수 있는 기술로 떠오르고 있다. 블록체인에 대한 관심이 높아지면서 선행 연구들은 블록체인 기술에 관련된 암호화폐와 적용방안에 대한 연구를 주로 수행하였다. 반면에 블록체인의 안정적인 구동에 대한 연구는 크게 주목하지 않았다. 대표적으로 블록체인의 엉클블록은 블록체인 시스템의 안정적 구동에 중요한 역할을 담당함에도 불구하고 이에 대한 연구는 거의 수행되지 않았다. 이러한 인식을 기반으로 본 연구는 블록체인 정보와 거시 경제 요인들을 활용하여 블록체인의 엉클블록을 머신러닝 기법으로 예측하고자 하였다. 인공신경망, 서포트벡터머신 분석 결과, 블록체인 정보와 거시 경제 요인들은 블록체인의 엉클블록 예측에 기여하는 것으로 나타났다. 또한, 블록체인 정보만을 활용한 인공신경망은 엉클블록의 발생을 예측하는데 가장 우수한 성능을 제공하는 것으로 나타났다. 본 연구는 정보시스템 분야에서 블록체인 연구를 주도하고 기여할 수 있는 방안을 제시한다.

Keywords

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