Public blockchains such as Bitcoin contain several hundred million financial transactions. Analysing them is of considerable interest for scientific research and commercial applications, but also for authorities in particular, as blockchain systems are also used for criminal payments due to their pseudonymity. Payment flows are concealed by users creating any number of "accounts" in the form of addresses within these systems.
An established forensic method in this context is address clustering, which uses heuristics to group the addresses per user in order to analyse their activities separately. Previous methods usually only analysed individual blockchains in single-chain analyses. However, these can be extended to cross-chain analyses by including the data from several blockchains.
In his master's thesis, Martin Plattner fundamentally expanded the high-performance blockchain analysis platform BlockSci developed at Princeton University to include a multi-chain mode in order to enable efficient cross-chain analyses of forked chains. Blockchain forks are forks of existing blockchains and are particularly suitable for cross-chain analyses due to their shared transaction history between parent and fork chain. A popular example of a fork is Bitcoin Cash, which split off from the Bitcoin blockchain in August 2017 and served as the object of his analysis in his master's thesis.
One of the main objectives was to find the same addresses across both blockchains in order to establish a connection between these addresses and their users. The new multi-chain mode enabled Martin Plattner to implement a new type of clustering method: cross-chain address clustering. This combines the activities of users across several forked chains to improve the quality of the clustering.
By including Bitcoin Cash in an existing Bitcoin clustering, he was able to identify over 570,000 additional cluster mergers as of December 2019. In total, over 30 million addresses were affected. The implementation is designed to be flexible so that the process can also be applied to other blockchain systems in the future.
Together with researchers from Princeton, Johns Hopkins and Cornell Tech, he successfully submitted the cross-chain address clustering method he developed for publication at the renowned IT security conference USENIX Security 2020. There are also plans to integrate his clustering method into the blockchain analysis software GraphSense. This is being developed as open source software by the Complexity Science Hub and the Austrian Institute of Technology, among others, and offered as an operational service by the spin-off Iknaio Cryptoasset Analytics GmbH.
Martin Plattner was one of the three prize winners who received their awards at the DEXA conference on 22 August 2022.