Using Degree Centrality to Identify Market Manipulation on Bitcoin

Autor(es)

Pereira, Daiane M. ; Couto, Rodrigo S. ; GarciaAlfaro, J ; MunozTapia, JL ; NavarroArribas, G ; Soriano, M

• Tipo de documento: Artigo Científico
• Fonte: DATA PRIVACY MANAGEMENT, CRYPTOCURRENCIES AND BLOCKCHAIN TECHNOLOGY, ESORICS 2021; v. 13140, p. 16-pg., 2022-01-01.

Resumo

In 2014, the Mt.Gox Bitcoin exchange had its internal dataset hacked and leaked. After that, some studies employ this dataset to evaluate if Mt.Gox was doing market manipulation on Bitcoin. Also, they identify patterns of this manipulation. Based on these studies, this paper analyzes the Bitcoin blockchain in the period where Mt.Gox was active. We model the transactions in the blockchain as a graph and evaluate the degree centrality of each node. We thus analyze how the ranking of nodes with the highest centrality values changes over time. Our conclusions indicate that top nodes are stable, but there is a period where it changes. To better understand this behavior, we simulate the insertion of transactions in the network and verify how the ranking changes. As a result, we provide indications that we can use ranking changes to detect malicious activities. We also show a case study using this ranking to predict abnormal behavior in the network. (AU)

• Processo FAPESP: 15/24494-8 - Comunicação e processamento de big data em nuvens e névoas computacionais
• Beneficiário: Nelson Luis Saldanha da Fonseca
• Modalidade de apoio: Auxílio à Pesquisa - Temático