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Blockchain: Breaking Bad: Data Analysis of Blockchain-User Interaction

Information on the Thesis

Type of Final Thesis: Bachelor, Master
Supervisor: Scott ThiebesKonstantin Pandl
Research Group: Critical Information Infrastructures

Archive Number: 4.490
Status of Thesis: Open

Further Information


Despite rapidly gaining popularity, Blockchain technology is challenging to use securely. Users have to deal with the management and interaction of nodes, private keys, exchanges, forks, among others. This potentially influences the behavior how they use the Blockchain and interact with the network, such as Bitcoin. As a public and transparent ledger, blockchain user behavior data can be observed and classified. State of the art data analysis methods includes machine learning (e.g. clustering) algorithms and cutting-edge heuristics. With the insights from these algorithms, research questions can be answered as to how certain user groups (e.g., small or large investors, miners, hackers) interact with Blockchain systems and how this interaction changes over time (e.g., due to certain events in the external world).


Possible topics include, but are not limited to:

  • Design and implementation of a data analysis framework for a certain Blockchain network (e.g., Bitcoin)
  • Design and implementation of machine-learning algorithms and heuristics to analyze blockchain transactions and cluster user behaviour
  • Creation and analysis of hypotheses about user’s interaction with blockchain networks

This is an umbrella topic since topics of interest change rapidly. The specific topic will be based on your interests and determined together with you. The thesis allows you to gain deep knowledge and experience in two rapidly growing fields, blockchain, and big data analysis.

Introductory literature:

Publication bibliography Fleder, Michael; Kester, Michael S.; Pillai, Sudeep (2015): Bitcoin transaction graph analysis. In arXiv preprint arXiv:1502.01657. Available online at

Gaihre, Anil; Luo, Yan; Liu, Hang (2018): Do bitcoin users really care about anonymity? an analysis of the bitcoin transaction graph. In : 2018 IEEE International Conference on Big Data (Big Data). IEEE, pp. 1198–1207. Available online at

Meiklejohn, Sarah; Pomarole, Marjori; Jordan, Grant; Levchenko, Kirill; McCoy, Damon; Voelker, Geoffrey M.; Savage, Stefan (2013): A fistful of bitcoins: characterizing payments among men with no names. In : Proceedings of the 2013 conference on Internet measurement conference. ACM, pp. 127–140. Available online at