Explainable Profiling Attacks on Ethereum Blockchain Users Based on Volumetric and Temporal Behaviour
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Tarih
2024
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IEEE
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
One of many different application areas of the blockchain technology is crypto-currencies. Products like Bitcoin and Solana provide financial services that are unmediated, distributed and anonymous. Among various blockchains, Ethereum stands out due to its support of smart contracts. However, softly authenticated transactions occuring on such platforms facilitate crimes like money laundering and sales of illegal items/services. Denanonymization, over blockchains, refers to identifying distinct accounts of the same person and is used for tracking illegal trafficking of cryptocurrencies. In this study, our purpose is to increase the rate of success of deanonymization and to support explainable approaches. Towards this aim, we imitate blockchain analysts and propose 19 novel heuristic features that are volumetric and temporal. Empirical experiments indicate that temporal features increase the attack success rate by 39%. Shapley values adapted from the cooperative game theory field support this finding.
Açıklama
32nd IEEE Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2024 -- Tarsus Univ Campus, Mersin, TURKEY
Anahtar Kelimeler
Ethereum blockchain, deanonymization, finance, game theory, explainable artificial intelligence (XAI)
Kaynak
32nd Ieee Signal Processing and Communications Applications Conference, Siu 2024
WoS Q Değeri
N/A
Scopus Q Değeri
0
