Blockchain Papers

Han Woo Park, Sejung Park

이 연구는 웹보메트릭스 빅데이터 기법을 활용한 암호화폐 온라인 영향력을 조사했다. 구체적으로 2017년 12월 시가총액 톱50개 화폐를 대상으로 온라인연결망을 측정했다. 웹보메트릭스에 기반한 빅데이터 분석을 실시해 암호화폐 홈페이지와 연결된 외부링크를 조사하여 각 암호화폐의 대중적 인지도를 파악하고, 나아가 암호화폐들의 관계적 특성을 분석했다. 연구결과 bitcoin.org, bitcoin.com, steemit.com의 온라인 영향력이 가장 강한 것으로 나타났다. 특히 steemit.com이 외부로부터의 링크 수가 가장 많았으며 상호링크 관계망에서 중개자의 위치를 점하고 있었다. bitcoin.org은 외향중심성 값이 가장 높게 나타나 적극적인 정보전송자로 자리매김하고 있는 반면 bitcoin.com은 내향중심성에서 1등을 차지하면서 권위적 정보허브로서 기능하고 있음을 발견했다. 나아가 사회연결망 지표와 와이스(Weiss) 평가점수와의 통계적 상관성을 발견하여 빅데이터 분석이 시장 예측도 가능하다는 것을 시사한다. 암호화폐를 둘러싼 정부규제가 계량화된 데이터 없이 주관적 비평과 정성적 측면에서 접근되면서 논란이 있는 가운데, 이 논문은 암호화폐의 현황을 웹보메트릭스 방법으로 측정하여 정책지원의 과학적 수단을 제공한다.This study explored presence and influence of cryptocurrencies on the web. A network of top 50 cryptocurrencies in terms of market capitalization was mapped on December 12, 2017. Webometric analytics was conducted to examine online presence and influence of each cryptocurrency as well as the relations between cryptocurrencies by tracing the external links from each site. The results suggest that bitcoin.org, bitcoin.com and steemit.com were the most influential sites based on the number of hit counts. Interestingly, steemit.com received the largest amount of links from other sites and bridged the sites of the other cryptocurrencies in the network. It is noteworthy that bitcoin.org with the highest outdegree centrality played a role as an active informant while bitcoin.com with the highest indegree centrality was a hub in the network. This study also found positive correlations between the results of Weiss ratings and key social network analysis indicators, including hit counts, Betweeness centrality, Out2Step, OutARD, InARD and 2StepBet. The result implies that webometric analytics is useful to predict a market. This data-driven approach to online influence and presence of cryptocurrencies is valuable to policy-makers who continue to debate about the societal impact and the regulations of cryptocurrencies.

Euiseok Kim

After Satoshi Nakamoto published ‘Bitcoin: A peer-to-peer electronic cash system’ in 2008, Blockchain has been GPT (General Purpose Technologies) that affect the whole cycle of the 4th Industrial Revolution. This study attempted to identify the innovativeness of Blockchain. Because of Blockchain’s ambidextrous characteristics, Blockchain has two kinds of innovativeness, technological innovation by physical technology and social innovation by social technology. Thus, this study will be useful to increase understanding and establishing strategy for Blockchain.

Lee Hee Jong, Cho Jae Young

No abstract is available for this record.

Jardar Tøn

The blockchain is one of the main mechanisms enabling Bitcoin to be a decentralized electronicpayment system. It provides the system with a shared transaction history, which can be verified byevery participant. With increased use, it has become apparent that there is limited possibility forscaling this to handle more transactions. Payment channel networks are one proposed solution tothis problem. They allow for more transactions to be done by moving some transactions to a sepa-rate network. The Lightning Network is one such network, which uses Bitcoin and the blockchain tooperate. While the transactions in this network will not be included in the blockchain, there will bedata there related to the network. This is because it needs the blockchain to manage the paymentchannels which the network consists of.In this project we have explored the blockchain with the goal of identifying transactions relatedto the Lightning Network, and by doing so, determine what information about it is available in theblockchain. We have created different methods for identifying these transactions. The methods usedifferent transaction characteristics differing in uniqueness, making some methods more precise,but having fewer results, and vice versa. We created software implementing the methods, whichwere used to parse the blockchain. The effectiveness of these methods have been quantified bycomparing the data we found when parsing the blockchain, to data we collected directly fromthe Lightning Network. The results shows that the methods are viable for identifying a subset oftransactions, and that precision can be sacrificed for finding more. By identifying these transactionswe were able to determine what information about the Lightning Network we can see from theblockchain perspective, and also some aspects where we are limited.We have also adapted heuristics from previous work doing blockchain analysis to our scenario.These were used to link related information we had found when parsing the blockchain, whichenabled us to create network graphs showing the relations between the Lightning Network channelsidentified on the blockchain. While the relations in this network graph were limited, comparedto the actual relations found within the lightning network, they show how the blockchain canbe used to infer non-explicit information about the lightning network. We have also identifiedseveral methods for potentially inferring or locating more information using what is available inthe blockchain.

Kim Soon Gohn

No abstract is available for this record.

Jungsuk Kim, Gwang-Yong Gim

No abstract is available for this record.

Jaehyun Lee, Yong-Duk Chi, Joong-Hyo Bok, Gwang-Yong Gim

No abstract is available for this record.

Shuyan Cao, Yanan Cao, Xiaoyu Wang, Yanqiao Lu

Analyzing 242 articles related to the study of blockchain which were published in China and abroad from 2014 to 2016, and from the aspects of literature sources, research subjects, research methods and western countries, the basic frame of blockchain research classification is put forward. Summarize the current blockchain technology progress, research limitations and future development trends. The research shows that the domestic research on the blockchain is more decentralized, non-systematic, and has not reached a certain research depth. What’s more, it is lack of quantitative analysis. Digital currency, Internet finance, and the risk of blockchain technology research will be the focus of future research.

Junpeng Wang, Xue Yubo, Minghao Liu

As the world's first completely decentralized digital payment system, the emergence of bitcoin represents a revolutionary phenomenon in financial markets. This paper mainly studies the fluctuations of bitcoin price and discusses weather digital currencies represented by bitcoin have the potential to invest. Cointegration analysis and VEC (Vector Error Correction) Model have been performed to demonstrate the relationship between bitcoin price and some variables including stock price index, oil price and daily trading volume of bitcoin. The empirical research indicates that there is long-term equilibrium and short-term dynamic relationship among the four factors. The short run analysis reveals that oil price and bitcoin trading volume have little influence on bitcoin price while stock price index has relatively larger impact on it. In the long run, stock price index and oil price have a negative effect on bitcoin price. On the contrary, the value of bitcoin is positively affected by daily trading volume.

Ki-Yeon Nam

No abstract is available for this record.

Il-Kwon Lim, Young-Hyuk Kim, Jae‐Gwang Lee, Jae-Pil Lee · 6 authors

No abstract is available for this record.

전웅렬, 이윤호, 원동호

2010년, Sebe 등은 원격 투표에 사용할 수 있는, 가벼우면서도 효율적인 믹스넷 방식을 제안하였다. 이 방식은 암호학적 해쉬연산 만을 이용하기 때문에 기존 방식처럼 복잡한 영지식증면(zero-knowledge proofs)이 필요없이 간단하면서도 믹스넷의 동작을 효율적으로 증명할 수 있는 장점이 있다. 본 논문에서는 Sebe 등이 이용한 가정 사항을 그대로 유지하면서 보다 효율적인 믹스넷을 제안한다.