Home | Graphsense Cryptoasset Analytics Platform

GraphSense is a cryptoasset analytics platform emphasizing full data sovereignty, algorithmic transparency, and scalability. GraphSense is open-source and free. It provides a dashboard for interactive investigations and, more importantly, complete data control for automatizing cryptoasset analytics workflows.

Supported Assets

The GraphSense system design supports UTXO- (e.g., Bitcoin) and account-model (e.g., Ethereum, Tron) ledgers. Currently, adapters are available for major cryptocurrencies like Bitcoin, Bitcoin Cash, Litecoin, Zcash, Ethereum and Tron. Additional ledgers can be integrated by implementing a lightweight adapter component.

Features

Cross-currency search
Search by address, tag, transaction or block in several cryptocurrency ledgers.
Traverse transactions
Navigate in transaction network abstractions computed from various ledgers.
Inspect metadata
Inspect statistical properties of nodes and edges.
Find paths
Automatically search for transaction paths connecting two nodes.
Programmable
Support for data-driven analytics via the REST API.
TagPacks
GraphSense organizes attribution tags in TagPacks, which can be public or private.
Future-proof
Built on Apache Spark and Cassandra for horizontal scalability.
Open source
The complete software stack is open source and MIT licensed.

System Description / White paper

Haslhofer, B., Stütz, R., Romiti, M., & King, R. (2021). GraphSense: A general-purpose cryptoasset analytics platform. Arxiv pre-print. (pdf)

@article{Haslhofer:2021a,
    title = {GraphSense: A General-Purpose Cryptoasset Analytics Platform}, 
    author = {Bernhard Haslhofer and Rainer Stütz and Matteo Romiti and Ross King},
    year = {2021},
    journal = {Arxiv pre-print},
    url = {https://arxiv.org/abs/2102.13613}
  }
  

Scientific Studies

GraphSense has already supported several scientific studies:

Stütz, R., Stockinger, J., Haslhofer, B., Moreno-Sanchez, P., & Maffei, M. (2022). Adoption and actual privacy of decentralized CoinJoin implementations in bitcoin. Proceedings of the 4st ACM conference on advances in financial technologies, AFT 2022, boston, september 19-22, 2022. (pdf)

Kappos, G., Yousaf, H., Stütz, R., Rollet, S., Haslhofer, B., & Meiklejohn, S. (2022). How to peel a million: Validating and expanding bitcoin clusters. 31st USENIX security symposium (USENIX security 22). (pdf)

Romiti, M., Victor, F., Moreno-Sanchez, P., Nordholt, P., Haslhofer, B., & Maffei, M. (2021). Cross-layer deanonymization methods in the lightning protocol. Financial cryptography and data security (FC 2021). (pdf)

Stütz, R., Gaži, P., Haslhofer, B., & Illum, J. (2020). Stake shift in major cryptocurrencies: An empirical study. Financial cryptography and data security (FC 2020). (pdf)

Paquet-Clouston, M., Romiti, M., Haslhofer, B., Charvat, T. Spams meet Cryptocurrencies: Sextortion in the Bitcoin Ecosystem Advances in Financial Technologies, 2019. (pdf)

Romiti, M., Judmayer, A., Zamyatin, A., Haslhofer, B. A Deep Dive into Bitcoin Mining Pools: An Empirical Analysis of Mining Shares. Workshop on the Economics of Information Security, 2019. (pdf)

Paquet-Clouston, M., Haslhofer, B., & Dupont, B. Ransomware payments in the bitcoin ecosystem. Journal of Cybersecurity, 5 (1). (pdf)

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)

Core Team

Bernhard Haslhofer, Complexity Science Hub Vienna

Rainer Stütz, Complexity Science Hub Vienna

Matthias Rella, Iknaio Cryptoasset Analytics GmbH

Michael Fröwis, Iknaio Cryptoasset Analytics GmbH

Thomas Niedermayer, Iknaio Cryptoasset Analytics GmbH

Melitta Dragaschnig, AIT - Austrian Insitute of Technology GmbH

Michael Seidl, AIT - Austrian Insitute of Technology GmbH