Forschung

Unser Institut beschäftigt sich mit einem breiten Themenspektrum wie Skalierbarkeit, Zuverlässigkeit, Sicherheit und Datenschutz, Selbstorganisation und Beherrschbarkeit von Komplexität in Verteilten Systemen in einer Vielzahl von Einsatzszenarien wie Cloud-Computing oder Fahrzeug-Fahrzeug-Kommunikation.

Lehre

In der Lehre decken wir das gesamte Spektrum von Rechnernetzen, über verteilte Systeme bis hin zu Sicherheit und Privacy-Schutz ab. Unsere noch offenen Abschlussarbeiten und Projektarbeiten finden Sie auf den entsprechenden Webseiten. Für Prüfungen beachten Sie bitte unsere Hinweise.

Soziale Medien

Unsere letzten Publikationen

Meißner, E., Kargl, F., Erb, B. and Engelmann, F. 2025. PrePaMS: Privacy-Preserving Participant Management System for Studies with Rewards and Prerequisites. Proceedings on Privacy Enhancing Technologies. 2025, 1 (2025). [accepted for publication]
Taking part in surveys, experiments, and studies is often compensated by rewards to increase the number of participants and encourage attendance. While privacy requirements are usually considered for participation, privacy aspects of the reward procedure are mostly ignored. To this end, we introduce PrePaMS, an efficient participation management system that supports prerequisite checks and participation rewards in a privacy-preserving way. Our system organizes participations with potential (dis-)qualifying dependencies and enables secure reward payoffs. By leveraging a set of proven cryptographic primitives and mechanisms such as anonymous credentials and zero-knowledge proofs, participations are protected so that service providers and organizers cannot derive the identity of participants even within the reward process. In this paper, we have designed and implemented a prototype of PrePaMS to show its effectiveness and evaluated its performance under realistic workloads. PrePaMS covers the information whether subjects have participated in surveys, experiments, or studies. When combined with other secure solutions for the actual data collection within these events, PrePaMS can represent a cornerstone for more privacy-preserving empirical research.
Heß, A., Hauck, F.J. and Meißner, E. 2024. Consensus-agnostic state-machine replication. 25th ACM/IFIP Int. Middleware Conf. (Hong Kong, China, Dec. 2024). [accepted for publication]
State-machine replication (SMR) is a popular fault-tolerance technique for building highly-available services. Usually, consensus protocols are used to enforce a deterministic service-request ordering among replicas, in order to prevent their state from diverging. Over the last decades, a multitude of consensus protocols have been developed which come with different characteristics but also with different communication and programming models. Our Consensus-Agnostic Replication Toolkit (CART) is a wrapper for consensus protocols that relieves clients from most consensus configuration and support. Besides, it implements a generic client and application interface to support different consensus protocols and configurations, e.g. in cloud deployments. CART has built-in authentication of services based on BLS threshold signatures. It can further prove malicious behaviour of replicas, thus speeding up recovery in case of Byzantine faults. We evaluate the performance overhead of our approach in a real-world WAN deployment for two different consensus protocol implementations using the YCSB benchmark. Our results show that CART is able to reach up to 90% of the throughput achieved by the native consensus protocol with an additional latency overhead of only 10%.
Hauck, F.J. and Heß, A. 2024. Linearizability and state-machine replication: Is it a match? ArXiv.org.
Bradatsch, L., Hermann, A. and Kargl, F. 2024. Attribute Threat Analysis and Risk Assessment for ABAC and TBAC Systems. In Proceedings of the 21st International Conference on Security and Cryptography (Jul. 2024), 26–39.
Schillings, C., Meißner, E., Erb, B., Bendig, E., Schultchen, D., Pollatos, O. and others 2024. Effects of a Chatbot-Based Intervention on Stress and Health-Related Parameters in a Stressed Sample: Randomized Controlled Trial. JMIR Mental Health. 11, 1 (May 2024), e50454.

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Kontakt

Sekretariat

Marion Köhler
Lysha Lewis
Email-Adresse Sekretariat
Telefon: +49 731 50-24140
Telefax: +49 731 50-24142

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Institut für Verteilte Systeme
Universität Ulm
Albert-Einstein-Allee 11
89081 Ulm

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