About This Topic
Bitcoin is the most prominent example of a virtual cryptocurrency. It is not issued by any government, bank, or organization but relies on cryptographic protocols and a distributed peer-to-peer network of users to mint, store, and transfer currency units.
The goal of the master thesis is to apply data science methods (clustering, anomaly detection) on large graphs extracted from the Bitcoin blockchain in order to provide insight into the structure (e.g., real-world actors) and dynamics of virtual currency ecosystems. The tasks to be carried out are:
● Conduct state-of-the-art research on data science methods applied in the context of virtual currencies ● Prototype and evaluate scaleable clustering and anomaly detection algorithms operating on the Bitcoin transaction graph using state-of-the art Data Science tools
● Basic experience with large-scale data analytics platforms (e.g., Apache Spark) ● Programming skills in Scala or Python ● Experience with R / Matlab / Octave ● Basic machine learning knowledge