Statistical modeling of individual agent behavior in blockchain-based systems

Supervisor(s)Dr. Svetlana Abramova


Economic and forensic analyses of public distributed ledgers become popular in the study of selected properties of blockchain-based systems. The aim of this thesis is to build a statistic model that predicts behavior of individual agents in such systems (e.g., wallet management) and calibrate the model using Bitcoin transaction data. A valid calibrated model can be the basis for decision support in the next generation of Bitcoin client software.

This thesis requires a student’s good understanding of Bitcoin and its operation, programming experience and interest in statistical modeling as well as profound data analysis skills.


  • Möser, M. and Böhme, R. Trends, Tips, Tolls: A Longitudinal Study of Bitcoin Transaction Fees. In M. Brenner, N. Christin, B. Johnson and K. Rohloff, eds., Financial Cryptography and Data Security, 2nd Workshop on BITCOIN Research. Lecture Notes in Computer Science 8976, Springer, Berlin Heidelberg, 2015, pp. 19–33. [PDF] [Publisher]
  • Möser, M. and Böhme, R. Anonymous Alone? Measuring Bitcoin’s Second-Generation Anonymization Techniques. In IEEE Security & Privacy on the Blockchain (IEEE S&B). Paris, France, 2017, pp. 32–41. [PDF]