arXiv subjects

Martin Harrigan

Publications and source records attributed to Martin Harrigan.

10 recordsLinked to original sources

arXiv2026

Mapping Partisan Fault Lines Within DAOs

Decentralised Autonomous Organisations (DAO) can fragment when partisan communities emerge within their governance structures, leading to organisational splits known as "forks". We present a method to detect these emerging communities by analysing on-chain voting behaviour before fragmentation occurs. Our approach extracts voting events from governance smart contracts, constructs voter matrices encoding participation patterns, and applies pairwise dissimilarity analysis to quantify ideological divergence between addresses. We visualise these relationships using multidimensional scaling and identify partisan communities through k-means clustering with silhouette score optimisation. Using Nouns DAO as a case study, a protocol that has experienced multiple documented forks, we demonstrate that addresses destined to fork cluster together months before actual fragmentation events. Our analysis of 330 proposals spanning from contract deployment to the first major fork shows that 90% of fork addresses cluster together in the final 44 proposals, compared to only 47% in randomised data. These results indicate that partisan communities can be detected and visualised through on-chain governance analysis, offering early warnings of emerging divisions before they cause organisational fragmentation.

cs.CR↗

arXiv2026

The On-Chain and Off-Chain Mechanisms of DAO-to-DAO Voting

Voting is the primary mechanism through which Decentralised Autonomous Organisations (DAOs) reach decisions. Although transparent, the voting process can be opaque: it can involve many interacting smart contracts. The nexus of the decision-making process can be relocated and the true voter demographic obfuscated. DAOs can also govern other DAOs, a process known as metagovernance. We present a method for identifying DAO-to-DAO metagovernance on the Ethereum blockchain. We focus on the links between DAOs and token contracts. We use a signature-matching algorithm to handle a variety of DAO frameworks and voting schemes. Once we establish token-to-DAO relationships, we gather and process voting data to produce a list of metagovernance relationships. We apply this algorithm to an initial set of sixteen DAOs and we extend the dataset as more DAOs are identified. We produce a metagovernance network with 61 DAOs and 72 metagovernance relationships. We examine three case studies that show metagovernance of various forms: strategic, decisive, and nexus, where a DAO becomes a governance hub for multiple other DAOs. We demonstrate that metagovernance obscures voting context and introduces entities driven by self-interest that can significantly influence governance. We highlight instances of metagovernance between DAOs operating on the Ethereum blockchain where current governance tools fail to reveal such dynamics. Better tools are needed to preserve the transparency-centric ethos of DAOs and mitigate risks associated with metagovernance.

cs.CR↗

arXiv2024

Token Composition: A Graph Based on EVM Logs

Tokens have proliferated across blockchains in terms of number, market capitalisation, and utility. Some tokens are tokenised versions of existing tokens, known variously as wrapped tokens, fractional tokens or shares. The repeated application of this process creates tokens with arbitrarily many layers of composition. We perform an empirical analysis of token composition on the Ethereum blockchain. We introduce a graph that represents the tokenisation of tokens by other tokens, and we show that the graph contains non-trivial topological structure. We relate properties of the graph, for example, connected components and cyclic structure, to the tokenisation process. For example, we identify the longest directed path and its corresponding sequence of tokens, and we visualise the connected components relating to a stablecoin and a non-fungible token protocol. Our goal is to explore and visualise what has been built with tokens, rather than propose new constructions.

cs.CR↗

arXiv2023

Emergent Outcomes of the veToken Model

Decentralised organisations use blockchains for governance: on-chain transactions allocate voting weight, publish proposals, cast votes, and enact the results. A key challenge is aligning the short-term outlook of pseudonymous voters with the long-term success of the organisation. The Vote-Escrowed Token (veToken) model attempts to resolve this tension by requiring voters to lock tokens of value for an extended period in exchange for voting weight. In this paper we describe the veToken model and analyse its emergent outcomes. We describe its implementation by Curve, a popular automated market maker for stablecoins, and the ecosystem of protocols built on top. We show that voting outcomes are strongly associated with the bribes set by higher-level protocols, and that the cost per vote varies depending on how it is acquired. The outcomes of the fortnightly votes held by Convex Finance closely track the distribution of bribes through voting markets such as Votium. Frax Finance, a stablecoin issuer, plays a central role even though it directly locks relatively few tokens with Curve; instead, it indirectly locks tokens through yield aggregators and purchases voting weight through voting markets. Although the veToken model in isolation is straightforward, it leads to complex and emergent outcomes. Decentralised organisations should consider these outcomes before adopting the model.

cs.GT↗

arXiv2020

The Bisq Decentralised Exchange: On the Privacy Cost of Participation

The Bisq Trade Protocol and the Bisq Decentralised Autonomous Organisation (DAO) are core components of Bisq, a decentralised cryptocurrency exchange. The Bisq Trade Protocol systematises the peer-to-peer trading of Bitcoin for other currencies and the Bisq DAO decentralises the governance and finance functions of the entire exchange. However, by following the Bisq Trade Protocol and interacting with the Bisq DAO, participants necessarily publish data to the Bitcoin blockchain and broadcast additional data to the Bisq peer- to-peer network. We examine the privacy cost to participants in sharing this data. Specifically, we use novel address clustering heuristics to construct the one-to-many mappings from participants to addresses on the Bitcoin blockchain and augment the address clusters with data stored within the Bisq peer-to-peer network. We describe address clustering heuristics for both the Bisq Trade Protocol and the Bisq DAO. We show that the heuristics aggregate activity performed by each participant: trading, voting, transfers, and so on. We identify instances where participants are operating under multiple aliases, some of which are real-world names. We identify the dominant transactors and their role in a two-sided market. We conclude with suggestions to better protect the privacy of participants in the future.

cs.CR↗

arXiv2018

Airdrops and Privacy: A Case Study in Cross-Blockchain Analysis

Airdrops are a popular method of distributing cryptocurrencies and tokens. While often considered risk-free from the point of view of recipients, their impact on privacy is easily overlooked. We examine the Clam airdrop of 2014, a forerunner to many of today's airdrops, that distributed a new cryptocurrency to every address with a non-dust balance on the Bitcoin, Litecoin and Dogecoin blockchains. Specifically, we use address clustering to try to construct the one-to-many mappings from entities to addresses on the blockchains, individually and in combination. We show that the sharing of addresses between the blockchains is a privacy risk. We identify instances where an entity has disclosed information about their address ownership on the Bitcoin, Litecoin and Dogecoin blockchains, exclusively via their activity on the Clam blockchain.

cs.CR↗

arXiv2018

The Unreasonable Effectiveness of Address Clustering

Address clustering tries to construct the one-to-many mapping from entities to addresses in the Bitcoin system. Simple heuristics based on the micro-structure of transactions have proved very effective in practice. In this paper we describe the primary reasons behind this effectiveness: address reuse, avoidable merging, super-clusters with high centrality, and the incremental growth of address clusters. We quantify their impact during Bitcoin's first seven years of existence.

cs.CR↗

arXiv2012

An Analysis of Anonymity in the Bitcoin System

Anonymity in Bitcoin, a peer-to-peer electronic currency system, is a complicated issue. Within the system, users are identified by public-keys only. An attacker wishing to de-anonymize its users will attempt to construct the one-to-many mapping between users and public-keys and associate information external to the system with the users. Bitcoin tries to prevent this attack by storing the mapping of a user to his or her public-keys on that user's node only and by allowing each user to generate as many public-keys as required. In this chapter we consider the topological structure of two networks derived from Bitcoin's public transaction history. We show that the two networks have a non-trivial topological structure, provide complementary views of the Bitcoin system and have implications for anonymity. We combine these structures with external information and techniques such as context discovery and flow analysis to investigate an alleged theft of Bitcoins, which, at the time of the theft, had a market value of approximately half a million U.S. dollars.

physics.soc-ph↗

arXiv2012

Identifying Discriminating Network Motifs in YouTube Spam

Like other social media websites, YouTube is not immune from the attention of spammers. In particular, evidence can be found of attempts to attract users to malicious third-party websites. As this type of spam is often associated with orchestrated campaigns, it has a discernible network signature, based on networks derived from comments posted by users to videos. In this paper, we examine examples of different YouTube spam campaigns of this nature, and use a feature selection process to identify network motifs that are characteristic of the corresponding campaign strategies. We demonstrate how these discriminating motifs can be used as part of a network motif profiling process that tracks the activity of spam user accounts over time, enabling the process to scale to larger networks.

cs.SI↗

arXiv2012

Network Analysis of Recurring YouTube Spam Campaigns

As the popularity of content sharing websites such as YouTube and Flickr has increased, they have become targets for spam, phishing and the distribution of malware. On YouTube, the facility for users to post comments can be used by spam campaigns to direct unsuspecting users to bogus e-commerce websites. In this paper, we demonstrate how such campaigns can be tracked over time using network motif profiling, i.e. by tracking counts of indicative network motifs. By considering all motifs of up to five nodes, we identify discriminating motifs that reveal two distinctly different spam campaign strategies. One of these strategies uses a small number of spam user accounts to comment on a large number of videos, whereas a larger number of accounts is used with the other. We present an evaluation that uses motif profiling to track two active campaigns matching these strategies, and identify some of the associated user accounts.

cs.SI↗