Process Mining for Decentralized Applications

Abstract

Distributed Ledger Technologies and particularly Blockchain-based Decentralized Applications entail transaction data from various use cases and usage behaviors in a decentralized manner. In this context, we propose to apply Process Mining as a means to understand and quantify how a Distributed Ledger is de facto utilized. This paper introduces a heuristic Process Mining approach for extracting high level process structures from Distributed Ledgers and Decentralized Applications, which can also represent changes over time. The universal approach is demonstrated on the basis of the complete set of all transactions that happened on the Ethereum Blockchain during its first three years. Events, cases, and activities allow to compile an evolutionary time line, which shows the Blockchain evolving from its early stages to broader adoption. Furthermore, measures of activity significance, confidence, and process complexity are used to compile dependency graphs, which represent process transitions.