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This study investigates the use of process mining in conjunction with blockchain data analysis to enhance transparency and detect market anomalies in decentralised applications. Using CryptoKitties as a case study, a game built around Non-Fungible Tokens (NFTs), we analyse transaction data to identify hidden patterns and irregularities indicative of unethical practices, including black-market activity and price manipulation. This highlights gaps in blockchain governance models and how audit supported by process and data analytics can help address them.

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Suspicious Activity Detection Using Blockchain Process Mining

  • 会议论文

  • 发表日期：

    2025年

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  • Felipe Alejandro Manzor Manzor,
  • Adam Burke,
  • Nagarajan Venkatachalam,
  • Andrzej Janusz

摘要

This study investigates the use of process mining in conjunction with blockchain data analysis to enhance transparency and detect market anomalies in decentralised applications. Using CryptoKitties as a case study, a game built around Non-Fungible Tokens (NFTs), we analyse transaction data to identify hidden patterns and irregularities indicative of unethical practices, including black-market activity and price manipulation. This highlights gaps in blockchain governance models and how audit supported by process and data analytics can help address them.