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3/22/2018

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GraphSense - Blockchain Analytics

by John Doe

GraphSense is an open source platform for analyzing cryptocurrenciessuch as Bitcoin. Address Clustering: partition the set of addresses observed in a cryptocurrencyecosystem into maximal subsets (clusters) that are likely to be controlled by the samereal-world entity. Micro- and Macroscopic Analysis: inspect main cryptocurrency entities(block, transaction, address) and compute summary statistics over the entireblockchain. Network Perspective: apply a network-centric perspective and traverse currencyflows between addresses and clusters. Horizontal Scalability: cryptocurrency blockchains are growingand new currencies appear on the horizon. To make GraphSensefuture-proof, it is built on Apache Spark and Cassandra forhorizontal scalability. Technical ArchitectureGraphSense is built on scalable and distributed cluster technology and therefore requires a number of software components. They must be setup and/or executed in the following order: bitcoin-client: a Docker container encapsuling the most-recent Bitcoin client version datafeed: a component for ingesting raw blockchain data and exchange rates into Cassandra transformation: a Spark pipeline for computing statistics and network representations from raw blockchain data stored in Cassandra. rest-api: an API for retrieving data from the underlying Cassandra store dashboard: a user-interface allowing search, inspection, and traversal of cryptocurrency entities ExampleThe following example shows details about an example Bitcoin address.PublicationsSome more technical details about GraphSense are described here; please cite as:@inproceedings{Haslhofer:2016a, title={O Bitcoin Where Art Thou? Insight into Large-Scale Transaction Graphs.}, author={Haslhofer, Bernhard and Karl, Roman and Filtz, Erwin}, booktitle={SEMANTiCS (Posters, Demos)}, year={2016}}So far, GraphSense has been used for computing statistics in the followingscientific papers:Filtz, E., Polleres, A., Karl, R., Haslhofer, B.:Evolution of the Bitcoin Address Graph - An Exploratory Longitudinal Study.International Data Science Conference (DSC 2017), Salzburg, Austria, 2017.(pdf)ContributorsBernhard Haslhofer Roman Karl Mihai Bartha Rainer Stütz

Illustration Image

GraphSense is an open source platform for analyzing cryptocurrencies such as Bitcoin.

  • Address Clustering: partition the set of addresses observed in a cryptocurrency ecosystem into maximal subsets (clusters) that are likely to be controlled by the same real-world entity.

  • Micro- and Macroscopic Analysis: inspect main cryptocurrency entities (block, transaction, address) and compute summary statistics over the entire blockchain.

  • Network Perspective: apply a network-centric perspective and traverse currency flows between addresses and clusters.

  • Horizontal Scalability: cryptocurrency blockchains are growing and new currencies appear on the horizon. To make GraphSense future-proof, it is built on Apache Spark and Cassandra for horizontal scalability.

Technical Architecture

GraphSense is built on scalable and distributed cluster technology and therefore requires a number of software components. They must be setup and/or executed in the following order:

  • bitcoin-client: a Docker container encapsuling the most-recent Bitcoin client version

  • datafeed: a component for ingesting raw blockchain data and exchange rates into Cassandra

  • transformation: a Spark pipeline for computing statistics and network representations from raw blockchain data stored in Cassandra.

  • rest-api: an API for retrieving data from the underlying Cassandra store

  • dashboard: a user-interface allowing search, inspection, and traversal of cryptocurrency entities

Example

The following example shows details about an example Bitcoin address.

screenshot

Publications

Some more technical details about GraphSense are described here; please cite as:

@inproceedings{Haslhofer:2016a,
    title={O Bitcoin Where Art Thou? Insight into Large-Scale Transaction Graphs.},
    author={Haslhofer, Bernhard and Karl, Roman and Filtz, Erwin},
    booktitle={SEMANTiCS (Posters, Demos)},
    year={2016}
}

So far, GraphSense has been used for computing statistics in the following scientific papers:

Filtz, E., Polleres, A., Karl, R., Haslhofer, B.: Evolution of the Bitcoin Address Graph - An Exploratory Longitudinal Study. International Data Science Conference (DSC 2017), Salzburg, Austria, 2017. (pdf)

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