Decentralized Systems and Network Services Research Group
Under the term "Decentralized Systems and Network Services" we understand distributed and networked technical systems that span over more than one administrative domain. Hence, their operation depends on more than one party. Our research focuses on:
- Blockchains, broadcast and consensus algorithms and smart contracts
- P2P-networks and network monitoring
- Decentralized messaging at the example of Matrix
- Identity Management and Access Control Systems
- Secure and privacy-aware computing in partially trustworthy environments.
News | News Archive
At this year's Bitcoin Research Day, Hannes Hartenstein and Matthias Grundmann gave a talk titled "From Monitoring Bitcoin to Verifying Lightning: Modeling Aspects of the Bitcoin Universe". In particular, they presented our research on monitoring the P2P network of Bitcoin and on verification of the Lightning Network's protocol and discussed it with the participants.
The results of the BMWK-supported project SofDCar (Software-Defined Car) were presented to the public today at a technical expo in the Arena2036 in Stuttgart. Oliver Stengele was there and presented the project contributions of the research group to interested visitors. Within SofDCar, we examined the use of decentralized systems like Ethereum and the InterPlanetary File System to make the cooperation of parties along software supply chains more traceable and secure.
While there are already various proposals for peer-to-peer communication for the decentralized messaging middleware Matrix, these proposals require that the receiver and the originator are simultaneously online. We introduce relay-enhanced P2P Matrix (ReP2P Matrix) in order to improve message delivery between peers that are online at different times. We present our new publication on this topic, ReP2P Matrix: Decentralized Relays to Improve Reliability and Performance of Peer-to-Peer Matrix, on the first Decentralization of the Internet Workshop of this year's ACM CoNEXT. The publication is available as open access under CC-BY.
To support us in our daily lives, future humanoid assistant robots need both a certain degree of autonomy to learn and explore, but must also adhere to certain constraints. Constrained planning is a problem especially for otherwise promising approaches based on neural networks - while symbolic approaches are very good at adhering to constraints, but have trouble with complex, new environments. New developments in the area of neuro-symbolic AI would revolutionize constrained task planning. On this year's Symposium on Access Control Models and Technologies, we have presented our BlueSky publication “How to Raise a Robot - A Case for Neuro-Symbolic AI in Constrained Task Planning for Humanoid Assistive Robots” on that topic. The publication is freely available as open access under CC-BY.