Analysis of Arbitrary Content on Blockchain-Based Systems using BigQuery

TL;DR

This paper presents a cloud-based method to analyze and classify arbitrary content stored on public blockchains like Bitcoin and Ethereum, revealing usage patterns and potential abuse cases.

Contribution

It introduces a novel, adaptable approach for discovering and analyzing non-financial content on blockchains, including the first systematic comparison between Bitcoin and Ethereum.

Findings

Identified the types and volume of non-financial content on Bitcoin and Ethereum.

Provided insights into content-related usage patterns and abuse potential.

Compared data quality and quantity across different blockchain systems.

Abstract

Blockchain-based systems have gained immense popularity as enablers of independent asset transfers and smart contract functionality. They have also, since as early as the first Bitcoin blocks, been used for storing arbitrary contents such as texts and images. On-chain data storage functionality is useful for a variety of legitimate use cases. It does, however, also pose a systematic risk. If abused, for example by posting illegal contents on a public blockchain, data storage functionality can lead to legal consequences for operators and users that need to store and distribute the blockchain, thereby threatening the operational availability of entire blockchain ecosystems. In this paper, we develop and apply a cloud-based approach for quickly discovering and classifying content on public blockchains. Our method can be adapted to different blockchain systems and offers insights into content-related usage patterns and potential cases of abuse. We apply our method on the two most prominent public blockchain systems - Bitcoin and Ethereum - and discuss our results. To the best of our knowledge, the presented study is the first to systematically analyze non-financial content stored on the Ethereum blockchain and the first to present a side-by-side comparison between different blockchains in terms of the quality and quantity of stored data.