Analysis of Ethereum transactions during the prevention and investigation of criminal offenses
Abstract
The mechanism of Ethereum transactions analysis during the prevention and investigation of criminal offenses based on the study of modern experience in this area has been proposed. The directions of cryptocurrency use by offenders have been revealed. The relationship between the decrease of the cash market and the increase in the use of cryptocurrencies has been described. The state of legal regulation of cryptocurrencies in Ukraine has been studied. The insufficient regulation of the issue of handling cryptocurrencies in criminal proceedings has been emphasized. The issue of impossibility to seize cryptocurrency assets during criminal investigation has been raised. The problematic issues faced by law enforcement agencies in other countries when seizing cryptocurrencies have been outlined.
The structure and peculiarities of the cryptocurrency Ethereum circulation have been revealed. The features of the Ethereum platform and its distinctive features have been studied. The key standards that characterize the work of the Ethereum platform have been analyzed, explanations of key terms have been provided. The essential data in the blockchain for analysis have been highlighted, the procedure for accessing the Ethereum blockchain transactions has been described. Various web resources which one can access the Ethereum transaction blockchain through have been provided.
The purpose of email mixing, the conditions under which the anonymity of the email address is lost have been revealed. Some software tools used to analyze ethereum transactions have been evaluated by experiment. Automation of searching and building a schema of relations of different identifiers of e-transactions on the example of Maltego Community Edition and Crystal Expert have been demonstrated. Additional modules that need to be installed in Maltego Community Edition to analyze the relevant transactions effectively have been described.
It has been emphasized that when analyzing ethereum transactions, it is necessary to use not only ready-made tools, but also various scientific methods, such as identifying key criminal groups and wallets, identifying cases of money laundering using cryptocurrencies, additional address profiling, prevention of illegal behavior on the trading ethereum platform. The importance of effective analysis of cryptocurrencies for investigation has been described. The effectiveness of the Crystal Blockchain platform as a tool for analyzing Ethereum transactions in criminal investigations has been evaluated. The technical side of law enforcement training on the seizure of cryptocurrency assets has been revealed. For this purpose, it is recommended to use the so-called test networks. The mechanism of controlled transfer of cryptocurrency assets for custodial and non-custodial wallets has been proposed.
Downloads
References
Alotibi, J., Almutanni, B., Alsubait, T., Alhakami, H., & Baz, A. (2022). Money Laundering Detection using Machine Learning and Deep Learning. International Journal of Advanced Computer Science and Applications, 13(10), 732-738. https://doi.org/10.14569/IJACSA.2022.0131087.
Bryans, D. (2014). Bitcoin and Money Laundering: Mining for an Effective Solution. Indiana Law Journal, 89(1), 441-472.
Hendrickson, J. R., & Luther, W. J. (2022). Cash, crime, and cryptocurrencies. The Quarterly Review of Economics and Finance, 85, 200-207. https://doi.org/10.1016/j.qref.2021.01.004.
Lin, D., Wu, J., Xuan, Q., & Tse, C. K. (2022). Ethereum transaction tracking: Inferring evolution of transaction networks via link prediction. Physica A: Statistical Mechanics and its Applications, 600. https://doi.org/10.1016/j.physa.2022.127504.
Marchant, G. E. (2019). Emerging Technologies and the Courts. Court Review, 55(4), 146-153.
Nosov, V. V., & Manzhai, I. A. (2021). Certain Aspects of the Analysis of Cryptocurrency Transactions during the Prevention and Investigation of Crimes. Law and Safety, 1(80), 93-100. https://doi.org/10.32631/pb.2021.1.13.
Paquet-Clouston, M., Haslhofer, B., & Dupont, B. (2019). Ransomware payments in the Bitcoin ecosystem. Journal of Cybersecurity, 5(1). https://doi.org/10.1093/cybsec/tyz003.
Paschal Mgembe, I., Ladislaus Msongaleli, D., & Chaundhary, N. K. (2022, June 22). Progressive Standard Operating Procedures for Darkweb Forensics Investigation [Conference presentation abstract]. 10th International Symposium on Digital Forensics and Security, Istanbul, Turkey. https://doi.org/10.1109/ISDFS55398.2022.9800830.
Taylor, S. K., Ariffin, A., Zainol Ariffin, K. A., & Sheikh Abdullah, S. N. H. (2021, January 29-31). Cryptocurrencies Investigation: A Methodology for the Preservation of Cryptowallets [Conference presentation abstract]. 3rd International Cyber Resilience Conference, Langkawi Island, Malaysia. https://doi.org/10.1109/CRC50527.2021.9392446.
Taylor, S., Kim, S. H.-Y., Zainol Ariffin, K. A., & Sheikh Abdullah, S. N. H. (2022). A comprehensive forensic preservation methodology for crypto wallets. Forensic Science International: Digital Investigation, 42-43. https://doi.org/10.1016/j.fsidi.2022.301477.
Tironsakkul, T., Maarek, M., Eross, A., & Just, M. (2022a). Context matters: Methods for Bitcoin tracking. Forensic Science International: Digital Investigation, 42-43. https://doi.org/10.1016/j.fsidi.2022.301475.
Tironsakkul, T., Maarek, M., Eross, A., & Just, M. (2022b). The Unique Dressing of Transactions: Wasabi CoinJoin Transaction Detection [Conference presentation abstract]. EICC ‘22: Proceedings of the 2022 European Interdisciplinary Cybersecurity Conference. https://doi.org/10.1145/3528580.3528585.
Trozze, A., Davies, T., & Kleinberg, B. (2022). Explaining prosecution outcomes for cryptocurrency-based financial crimes. Journal of Money Laundering Control, 26(1). https://doi.org/10.1108/JMLC-10-2021-0119.
Wu, H., & Zheng, G. (2020). Electronic evidence in the blockchain era: New rules on authenticity and integrity. Computer Law & Security Review, 36. https://doi.org/10.1016/j.clsr.2020.105401.
Yadav, S. K., Sharma, K., Kumar, C., & Arora, A. (2022). Blockchain-based synergistic solution to current cybersecurity frameworks. Multimedia Tools and Applications, 81(25). https://doi.org/10.1007/s11042-021-11465-z.
Zhong, Z., Zhu, C., Yang, Y., Liao, X., Wang, R., Zhao, Y., Zhou, F., Shi, R., & Qin, Z. (2022). Money Laundering Detection for Cryptocurrency Transactions. Journal of Hunan University Natural Sciences, 49(10), 119-129. https://doi.org/10.16339/j.cnki.hdxbzkb.2022288.
Zhou, J., Yan, S., & Zhang, J. (2022, January 20-22). Prediction and analysis of illegal accounts on Ethereum based on Catboost algorithm [Conference presentation abstract]. International Conference on Big Data, Information and Computer Network, Sanya, China. https://doi.org/10.1109/BDICN55575.2022.00020.
Copyright (c) 2022 V. V. Nosov, O. V. Manzhai, Ye. V. Panchenko
This work is licensed under a Creative Commons Attribution 4.0 International License.