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With ongoing developments in the field of smart cities and digitalization in general, data is becoming a driving factor and value stream for new and existing economies alike. However, there exists an increasing centralization and monopolization of data holders and service providers, especially in the form of the big US-based technology companies in the western world and central technology providers with close ties to the government in the Asian regions. Self Sovereign Identity (SSI) provides the technical building blocks to create decentralized data-driven systems, which bring data autonomy back to the users. In this paper we propose a system in which the combination of SSI and token economy based incentivisation strategies makes it possible to unlock the potential value of data-pools without compromising the data autonomy of the users.
The set of transactions that occurs on the public ledger of an Ethereum network in a specific time frame can be represented as a directed graph, with vertices representing addresses and an edge indicating the interaction between two addresses.
While there exists preliminary research on analyzing an Ethereum network by the means of graph analysis, most existing work is focused on either the public Ethereum Mainnet or on analyzing the different semantic transaction layers using static graph analysis in order to carve out the different network properties (such as interconnectivity, degrees of centrality, etc.) needed to characterize a blockchain network. By analyzing the consortium-run bloxberg Proof-of-Authority (PoA) Ethereum network, we show that we can identify suspicious and potentially malicious behaviour of network participants by employing statistical graph analysis. We thereby show that it is possible to identify the potentially malicious
exploitation of an unmetered and weakly secured blockchain network resource. In addition, we show that Temporal Network Analysis is a promising technique to identify the occurrence of anomalies in a PoA Ethereum network.