GraphSense - Real-time Insight into Virtual Currency Ecosystems

B
Bernhard HaslhoferResearcher um University of Vienna
GraphSense

Real-time Insight into Virtual Currency Ecosystems
Bernhard Haslhofer, AIT - Austrian Institute of Technology
Austrian Data Forum (ADF)
Vienna, 2015-10-04
GraphSense - Real-time Insight into Virtual Currency Ecosystems
Bitcoin Ecosystem
• A virtual currency based on a P2P network
• Instant transactions worldwide
• No central authorities and control
• collective transaction management
• collective money issuance
• Public ledger of all transactions (block chain)
Goals
• Build algorithms and tools for gaining insight into
evolving virtual currency transaction graphs
• actor roles
• transaction patterns
• currency unit flows
• network topology
• anomalies
Approach
Scalable Anomaly
Detection Algorithms
(WP3)
Cross Data Source
Graph Construction
(WP2)
Open
Data
Data
Streaming
(WP1)
Private
Data
Large-Scale Distributed Data Processing Platform
Machine Learning and
Data Mining Libraries
Graph Analytics
Frameworks
GraphSense Analytics Dashboard (WP 4)
Project Key Facts
• Duration: 01.09.2015 - 30.08.2017 (24
months)
• Partners:
• AIT - Austrian Institute of Technology
• Braintribe IT Technologies GmbH
• WU Wien - Institute for Information
Business
• Funding: FFG - IKT der Zukunft
• Contact: bernhard.haslhofer@ait.ac.at
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GraphSense - Real-time Insight into Virtual Currency Ecosystems

  • 1. GraphSense
 Real-time Insight into Virtual Currency Ecosystems Bernhard Haslhofer, AIT - Austrian Institute of Technology Austrian Data Forum (ADF) Vienna, 2015-10-04
  • 3. Bitcoin Ecosystem • A virtual currency based on a P2P network • Instant transactions worldwide • No central authorities and control • collective transaction management • collective money issuance • Public ledger of all transactions (block chain)
  • 4. Goals • Build algorithms and tools for gaining insight into evolving virtual currency transaction graphs • actor roles • transaction patterns • currency unit flows • network topology • anomalies
  • 5. Approach Scalable Anomaly Detection Algorithms (WP3) Cross Data Source Graph Construction (WP2) Open Data Data Streaming (WP1) Private Data Large-Scale Distributed Data Processing Platform Machine Learning and Data Mining Libraries Graph Analytics Frameworks GraphSense Analytics Dashboard (WP 4)
  • 6. Project Key Facts • Duration: 01.09.2015 - 30.08.2017 (24 months) • Partners: • AIT - Austrian Institute of Technology • Braintribe IT Technologies GmbH • WU Wien - Institute for Information Business • Funding: FFG - IKT der Zukunft • Contact: bernhard.haslhofer@ait.ac.at