Towards a better identification of Bitcoin actors by supervised learning

Tubino, Rafael Ramos; Robardet, Céline; Cazabet, Rémy

doi:10.1016/j.datak.2022.102094

Cited by 2 publications

(1 citation statement)

References 17 publications

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“…Several heuristics exist for change address identification. The most straightforward approach is to consider the sole new address among the two output addresses of a transaction as the change address [48].…”

Section: Entity Recognitionmentioning

confidence: 99%

Exploring Blockchain Data Analysis and Its Communications Architecture: Achievements, Challenges, and Future Directions: A Review Article

M. Marhoon,

Basil,

Ma'arif

2023

IJRCS

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Blockchain technology is relatively young but has the potential to disrupt several industries. Since the emergence of Bitcoin, also known as Blockchain 1.0, there has been significant interest in this technology. The introduction of Ethereum, or Blockchain 2.0, has expanded the types of data that can be stored on blockchain networks. The increasing popularity of blockchain technology has given rise to new challenges, such as user privacy and illicit financial activities, but has also facilitated technical advancements. Blockchain technology utilizes cryptographic hashes of user input to record transactions. The public availability of blockchain data presents a unique opportunity for academics to analyze it and gain a better understanding of the challenges in blockchain communications. Researchers have never had access to such an opportunity before. Therefore, it is crucial to highlight the research problems, accomplishments, and potential trends and challenges in blockchain network data analysis and communications. This article aims to examine and summarize the field of blockchain data analysis and communications. The review encompasses the fundamental data types, analytical techniques, architecture, and operations related to blockchain networks. Seven research challenges are addressed: entity recognition, privacy, risk analysis, network visualization, network structure, market impact, and transaction pattern recognition. The latter half of this section discusses future research directions, opportunities, and challenges based on previous research limitations.

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Section: Entity Recognitionmentioning

confidence: 99%

Exploring Blockchain Data Analysis and Its Communications Architecture: Achievements, Challenges, and Future Directions: A Review Article

M. Marhoon,

Basil,

Ma'arif

2023

IJRCS

View full text Add to dashboard Cite

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Fingerprinting Bitcoin entities using money flow representation learning

Tovanich,

Cazabet

2023

Appl Netw Sci

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Deanonymization is one of the major research challenges in the Bitcoin blockchain, as entities are pseudonymous and cannot be identified from the on-chain data. Various approaches exist to identify multiple addresses of the same entity, i.e., address clustering. But it is known that these approaches tend to find several clusters for the same actor. In this work, we propose to assign a fingerprint to entities based on the dynamic graph of the taint flow of money originating from them, with the idea that we could identify multiple clusters of addresses belonging to the same entity as having similar fingerprints. We experiment with different configurations to generate substructure patterns from taint flows before embedding them using representation learning models. To evaluate our method, we train classification models to identify entities from their fingerprints. Experiments show that our approach can accurately classify entities on three datasets. We compare different fingerprint strategies and show that including the temporality of transactions improves classification accuracy and that following the flow for too long impairs performance. Our work demonstrates that out-flow fingerprinting is a valid approach for recognizing multiple clusters of the same entity.

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Towards a better identification of Bitcoin actors by supervised learning

Cited by 2 publications

References 17 publications

Exploring Blockchain Data Analysis and Its Communications Architecture: Achievements, Challenges, and Future Directions: A Review Article

Exploring Blockchain Data Analysis and Its Communications Architecture: Achievements, Challenges, and Future Directions: A Review Article

Fingerprinting Bitcoin entities using money flow representation learning

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