Cryptocurrency User Deanonymization via Bank Transfer Correlation
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Solution Overview
Problem
The anonymity of cryptocurrency transactions on distributed ledgers like blockchain hinders anti-money laundering efforts, as it is difficult to identify users involved in criminal activities, as transactions are pseudonymous and lack real-time tracking.
Innovation Solution
A computerized method and system that analyzes bank transfers to cryptocurrency exchanges, monitoring transactions and assigning probabilities to match anonymous blockchain transactions with real users, using currency transfer data, transaction sizes, exchange prices, and time intervals to deanonymize users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cryptocurrency transactions are recorded on distributed ledgers with pseudonymous user IDs, then user anonymity is maintained, but the ability to identify users involved in criminal activities is hindered
Solution Approach 1:
The patent uses cryptocurrency exchanges as intermediary entities to bridge the gap between anonymous blockchain transactions and real-world identities. By monitoring and analyzing transactions that pass through exchanges (which require KYC verification), the system can infer the identities of users involved in suspicious activities without directly compromising blockchain anonymity. The exchange acts as a mediator that connects pseudonymous blockchain addresses to verified user identities.
Solution Approach 2:
The system performs preliminary analysis of bank transfer data and cryptocurrency exchange transactions before investigating suspicious activities. By pre-establishing connections between bank accounts, exchange transactions, and blockchain addresses through proactive monitoring and data correlation, the system prepares identification information in advance, enabling rapid response when criminal activities are detected.
2Difficulty of detecting and measuring
If bank transfer data and cryptocurrency exchange transactions are analyzed to identify users, then user identification capability is improved, but data processing complexity increases
Solution Approach 1:
The patent divides the complex deanonymization process into distinct modular segments: (1) collecting bank transfer data, (2) monitoring cryptocurrency exchange transactions, (3) analyzing blockchain transactions, (4) correlating data across sources, and (5) generating identification results. Each module handles a specific aspect of the analysis independently, making the overall complex system more manageable and maintainable while improving identification capability.
Solution Approach 2:
The system employs a multi-functional analysis platform that can simultaneously process and correlate multiple types of data (bank transfers, exchange transactions, blockchain data) using a unified approach. This universal platform handles diverse data formats and sources through standardized processing pipelines, reducing overall system complexity despite the multifaceted nature of the identification task.
3Reliability
If real-time monitoring of transactions is implemented, then suspicious activity detection is enhanced, but processing time and computational resources increase
Solution Approach 1:
The system implements periodic batch processing of transaction data combined with real-time alerting for high-risk patterns. Instead of continuously analyzing every transaction in real-time, the system periodically processes aggregated data while maintaining real-time monitoring capabilities for predefined suspicious patterns, thereby balancing detection reliability with processing efficiency and time consumption.
Data Source
AI summary
A computerized method for deanonymizing cryptocurrency users by analyzing bank transfers to a cryptocurrency exchange may include receiving data from a currency transfer made by a user at a bank to a cryptocurrency exchange. Candidate currency exchange transactions made by the user may be identified from the currency exchange transactions completed by the cryptocurrency exchange within a predefined time interval. A set of anonymous transactions in blockchain cryptocurrency ledger in the predefined time interval may be identified where the cryptocurrency value in transactions of anonymous users in a blockchain cryptocurrency ledger matches a currency transfer amount made by the user in the candidate currency exchange transactions. Anonymous transactions in the set may be identified as being made by the user based on the probability assigned to each anonymous transaction in the set.