Methods and means of deanonymization of transactions in blockchain
DOI:
https://doi.org/10.30837/rt.2021.4.207.04Keywords:
Blockchain, transaction, consensus, anonymity, deanonymizationAbstract
This paper presents the results of a study of the properties of transactions formation and processing of in blockchain systems, aimed to identify existing barriers to the secure functioning of the network, processing and transmission of data between users, and to determine possible means of deanonymizing transactions. The anonymity of the network is one of the reasons for cryptocurrencies popularity and widespread use of blockchain technology. However, its presence is the basis for unscrupulous transactions, criminal actions of fraudsters and attacks on the system. Therefore, one of the main issues today is to ensure the reliable storage of information and the ability to track suspicious activity and timely protection of users in blockchain systems. The article examines known methods of increasing anonymity and maintaining confidentiality in modern networks based on the principles of blockchain technology, the threats arising from their use and the possible ways of tracking the actions of system participants. A comparative description of known tracking tools and possible means of de-anonymization of the history of completed transactions is given. As a result of the study, it was proposed to use a separate platform to analyze the network in real time, identify threats and their timely elimination, with the ability to visualize relationships and build address graphs as a result of tracking the entire chain of transactions. The tool makes it possible to implement a search among cryptocurrency addresses, blocks, transactions and tags, as well as to identify clusters associated with a particular address. The system analyzes the network in real time to gain insight into the statistics. Particular attention is paid to detecting so-called anomalies, i.e., the identification of transactions that deviate from standard structures. This allows identifying and tracking potentially malicious activities at an early stage.
References
Rui Zhang, Rui Xue, Ling Liu. Security and Privacy on Blockchain // ACM Computing Surveys. 2019. Vol. 52, No. 3, Article 51. 34 p.
Distributed Ledger Technology: beyond block chain. A report by the UK Government Chief Scientific Adviser, 2016. 88 p.
Aaron Wright, Primavera De Filippi. Decentralized Blockchain Technology and the Rise of Lex Cryptographia, 2015. 58 p.
Колесников П.И., Бекетнова Ю.М., Крылов Г.О. Технология блокчейн. Анализ атак, стратегии защиты. 2017. 67 p.
What is blockchain security? IBM: веб-сайт. URL: https://www.ibm.com/topics/blockchain-security
Transactions in the BTC blockchain. EXMO: веб-сайт. URL: https://info.exmo.me/en/education/transactions-in-btc-blockchain/
A Survey on the Adoption of Blockchain in IoT: Challenges and Solutions / M.A. Uddin and others. Blockchain: Research and Applications, 2021. 80 p.
Harry Halpin, Marta Piekarska. Introduction to Security and Privacy on the Blockchain. IEEE European Symposium. 2017. 3 p.
Бедрій Т. А., Ісмайлов К. Ю., Медведенко С. В. Використання знань про особливості криптовалют у протидії злочинності // Кібербезпека в Україні: правові та організаційні питання: матеріали ІІІ Всеукр. наук.-практ. конф. Одеса, 2018. С. 140-144.
Androulaki E., Karame G. O., Roeschlin M., Scherer T., & Capkun S. Evaluating user privacy in Bitcoin // Financial Cryptography and Data Security – 17th International Conference, FC 2013, Revised Selected Papers. Vol. 7859 LNCS, pp. 34-51.
Philip Koshy, Diana Koshy, and Patrick McDaniel. An analysis of anonymity in bitcoin using p2p network traffic. 2014. Financial Cryptography, 2014.
Biryukov A., Khovratovich D., Pustogarov I. Deanonymisation of clients in Bitcoin P2P network, CoRR, Vol. abs, 2014.
Офіційний веб-сайт Blockchain Explorer. URL: https://www.blockchain.com/en/explorer
Офіційний веб-сайт Matbea.net. URL: https://matbea.net/
Офіційний веб-сайт ORS CryptoHound. URL: https://www.c-hound.ai/
Офіційний веб-сайт Glassnod. URL: https://studio.glassnode.com/
Bernhard Haslhofer and others. GraphSense: A General-Purpose Cryptoasset Analytics Platform. 2021. 16 p.
Офіційний сайт GraphSense. URL: https://graphsense.info/
Данильчук Р. К., Жураковська О. С. Задача кластеризації адрес в мережі Блокчейн // Міжнар. наук. журнал «Інтернаука». Київ, 2018. № 9(49). Т. 1. С. 43-46.
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