Co-Pierre Georg

Sabine Bertram, Co-Pierre Georg

Blockchain has the potential to revolutionize the way we store, use, and process data. Information on most blockchains can be viewed by every node hosting the blockchain, which means that most blockchains cannot handle private data. Decentralized databases exist that guarantee privacy by encrypting user data with the user's private key, but this prevents easy data sharing. However, in many real world applications, from student data to medical records, it is desirable that user data is anonymously searchable. In this paper we present a novel system that gives users ownership over their data while at the same time enabling them to make their data searchable within previously agreed upon limits. Our system implements a strong notion of ownership using a self-sovereign identity system and a weak notion of ownership using multiple centralized databases together with a blockchain and a tumbling process. We discuss applications of our methods to university's student records and medical data.

Christoph Aymanns, Jakob Foerster, Co-Pierre Georg et al.

We propose multi-agent reinforcement learning as a new method for modeling fake news in social networks. This method allows us to model human behavior in social networks both in unaccustomed populations and in populations that have adapted to the presence of fake news. In particular the latter is challenging for existing methods. We find that a fake-news attack is more effective if it targets highly connected people and people with weaker private information. Attacks are more effective when the disinformation is spread across several agents than when the disinformation is concentrated with more intensity on fewer agents. Furthermore, fake news spread less well in balanced networks than in clustered networks. We test a part of our findings in a human-subject experiment. The experimental evidence provides support for the predictions from the model, suggesting that the model is suitable to analyze the spread of fake news in social networks.