Privacy-Preserving for UTXO-Based Smart City Ledgers

Abstract

In recent years, the distributed ledger systems (DLS) has become an indispensable approach for creating anonymous payment systems in Smart City infrastructures (in transportation and industrial systems, energy planting and distribution, etc.). Although users in such systems are identified indirectly, but through cryptographic protocols, there is a class of attacks aimed at deanonymizing participants by analyzing transactions and constructing a graph of relationships between addresses. To implement these attacks, intruders use statistical analysis methods, graph theory, and specialized utilities for comparing data from external sources, such as exchanges. An analysis of related works in this domain has shown that compromising cryptographic primitives is not a prerequisite for deanonymizing DLS users; in some cases, analyzing public ledger data and the behavioral characteristics of DLS participants is sufficient. The goal of this research is to preserve privacy and develop protocols that minimize the risks of deanonymizing participants in Smart City ledgers built on the UTXO model. This paper presents a developed framework consisting transaction generator, an analyzer for modeling deanonymization attacks, and protocols designed to protect against such attacks. The experimental study has shown that the use of the CoinJoin protocol significantly complicates the deanonymization task and leads to a decrease in the deanonymization accuracy.