Complex Network Analysis of the Bitcoin Transaction Network

Tao, Bishenghui; Dai, Hong-Ning; Wu, Jiajing; Ho, Ivan Wang‐Hei; Zheng, Zibin; Cheang, Chak Fong

doi:10.1109/tcsii.2021.3127952

Cited by 28 publications

(11 citation statements)

References 24 publications

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“…In the federated settings, models with local data characteristics replace the original data for transmission and aggregation, and after several rounds of training, a global model with all data features is obtained. For mobile edge computing, combining blockchain with deep reinforcement learning, the performance of computation offloading could be increased [76], and bitcoin network could be used to enhance complex network analysis [89].…”

Section: B Benefits To Artifical Intelligencementioning

confidence: 99%

When Digital Economy Meets Web3.0: Applications and Challenges

Chen

Zhang

et al. 2022

IEEE Open J. Comput. Soc.

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With the continuous development of web technology, Web 3.0 has attracted a considerable amount of attention due to its unique decentralized characteristics. The digital economy is an important driver of high-quality economic development and is currently in a rapid development stage. In the digital economy scenario, the centralized nature of the Internet and other characteristics often bring about security issues such as infringement and privacy leakage. Therefore, by exploring the digital economy and Web 3.0, it is necessary to investigate how to use Web 3.0 technologies to solve the pain points encountered in the development of the digital economy. In this paper, we discuss the aspects of Web 3.0 that should be integrated with the digital economy to better find the entry point to solve the problems by examining the latest advances of Web 3.0 in machine learning, finance, and data management. We hope this research will inspire those involved in academia and industry and help build a favourable ecology for the digital economy.

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Section: B Benefits To Artifical Intelligencementioning

confidence: 99%

When Digital Economy Meets Web3.0: Applications and Challenges

Chen

Zhang

et al. 2022

IEEE Open J. Comput. Soc.

Self Cite

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“…There are a number of studies on blockchain data analytics on Ethereum and Bitcoin [44,45,46,47,48,49,50,51,52]. Most of them focus on user behaviors, cryptocurrency flows, and scams of blockchains.…”

Section: Eosio Analysismentioning

confidence: 99%

Unravelling Token Ecosystem of EOSIO Blockchain

Zheng¹,

Liu²,

Dai³

et al. 2022

Preprint

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Being the largest Initial Coin Offering project, EOSIO has attracted great interest in cryptocurrency markets. Despite its popularity and prosperity (e.g., 26,311,585,008 token transactions occurred from June 8, 2018 to Aug. 5, 2020), there is almost no work investigating the EOSIO token ecosystem. To fill this gap, we are the first to conduct a systematic investigation on the EOSIO token ecosystem by conducting a comprehensive graph analysis on the entire on-chain EOSIO data (nearly 135 million blocks). We construct token creator graphs, token-contract creator graphs, token holder graphs, and token transfer graphs to characterize token creators, holders, and transfer activities. Through graph analysis, we have obtained many insightful findings and observed some abnormal trading patterns. Moreover, we propose a fake-token detection algorithm to identify tokens generated by fake users or fake transactions and analyze their corresponding manipulation behaviors. Evaluation results also demonstrate the effectiveness of our algorithm.

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“…In the federated settings, models with local data characteristics replace the original data for transmission and aggregation, and after several rounds of training, a global model with all data features is obtained. For mobile edge computing, combining blockchain with deep reinforcement learning, the performance of computation offloading could be increased [78], and the bitcoin network could be used to enhance complex network analysis [91].…”

Section: B Benefits To Artifical Intelligencementioning

confidence: 99%

When Digital Economy Meets Web3.0: Applications and Challenges

Chen¹,

Zhang²,

Li³

et al. 2022

Preprint

View full text Add to dashboard Cite

With the continuous development of web technology, Web3.0 has attracted a considerable amount of attention due to its unique decentralized characteristics. The digital economy is an important driver of high-quality economic development and is currently in a rapid development stage. In the digital economy scenario, the centralized nature of the Internet and other characteristics usually bring about security issues such as infringement and privacy leakage. Therefore, it is necessary to investigate how to use Web3.0 technologies to solve the pain points encountered in the development of the digital economy by fully exploring the critical technologies of digital economy and Web3.0. In this paper, we discuss the aspects of Web3.0 that should be integrated with the digital economy to better find the entry point to solve the problems by examining the latest advances of Web3.0 in machine learning, finance, and data management. We hope this research will inspire those who are involved in both academia and industry, and finally help to build a favourable ecology for the digital economy.

show abstract

Complex Network Analysis of the Bitcoin Transaction Network

Cited by 28 publications

References 24 publications

When Digital Economy Meets Web3.0: Applications and Challenges

When Digital Economy Meets Web3.0: Applications and Challenges

Unravelling Token Ecosystem of EOSIO Blockchain

When Digital Economy Meets Web3.0: Applications and Challenges

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