Amarasinghe, N. (2022). Systematic modelling of anonymity with application to cryptocurrencies. Unpublished PhD thesis, Queensland University of Technology.
Added by: Jack (2/21/23, 4:32 AM) Last edited by: Jack (2/21/23, 4:34 AM)
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Abstract
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The modern financial world has seen a significant rise in the use of cryptocurrencies in recent years, due to inherent convincing characteristics such as decentralised nature and convenience, and more importantly, perceived privacy and anonymity features. Despite being considered as the most widespread among all, Bitcoin is claimed to have significant lapses in relation to its anonymity. Many studies have shown that a majority of transactions can be traced back to their corresponding participants through the analysis of publicly available data, to which the cryptographic community has responded by proposing new constructions with improved anonymity claims. With the emergence of such new cryptocurrencies, many have attempted to evaluate such claims. These efforts have resulted in various interpretations of anonymity, which are often restricted to a particular currency scheme only. The absence of a common formalised metric for evaluating anonymity has led to much confusion over their claims, making it infeasible to properly compare different systems. More importantly, anonymity in such complex multi-party systems as finance, turns out to be a surprisingly multifaceted notion which needs to be defined and modelled with precision. In this work, we introduce a common framework, which can be used to evaluate the nature and extent of anonymity in (crypto)currencies and similar distributed transaction systems, irrespective of their implementation. For this purpose, we construct a theoretical model to represent the generic functionality of cryptocurrency schemes across different implementations, by establishing a cryptographically sound and secure foundation. We then develop a comprehensive adversarial model in order to capture different aspects of anonymity around system entities. Building upon this foundation, we formulate a common template, which is capable of modelling a multitude of different attacker scenarios with respect to various anonymity considerations. With an aim to strengthen the usability of this framework, we provide formal definitions for anonymity notions pertaining to various scenarios. In addition, we investigate the relationships among those definitions and formulate a set of theorems indicating the implications, dependencies and separations among them. Accordingly, this framework, together with the formal definitions and theorems, provides a means for modelling anonymity uniformly across different constructions. As such, the fine-grained systematisation of anonymity resulting from this work highlights the importance of precise definitions for modelling anonymity, which is a surprisingly nuanced concept.
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