Dr. Benjamin Erb

Welcome! My name is Benjamin Erb and I am a computer scientist primarily working in the field of distributed systems and interdisciplinary projects, especially with researchers from psychology.

I am currently employed as a researcher at the Institute of Distributed Systems, Ulm University. I hold a Diploma degree in Computer Science in Media and a Bachelor degree in Psychology from Ulm University. In 2019, I received my doctoral degree for my work on a novel live graph computing approach that combines concepts of traditional graph computing with features from event-driven architectures.

Main Research Interests

I have a strong interest in the design and implementation of data-intensive architectures, in particular distributed platforms for data processing. This includes processing models and programming abstractions for special data (e.g., evolving graph structures) as well as underlying platform architectures that aim for proper performance and scalability. I take special interest in data-intensive systems that consume stream-based input data and provide temporal capabilities such as retrospection. Here, I am using techniques such as event sourcing to enable history-aware processing.
A second research interest addresses the interaction between data privacy and psychology. On the one hand, this includes the tension field between confidentiality, data protection, and empirical research in psychology. Here, I am exploring potential threats to privacy from public research data sets due to the open science movement, but also technical solutions and mitigations based on privacy-enhancing technologies. On the other hand, I am also interested in psychological aspects of privacy to better understand user behavior when it comes to privacy decisions.

Updates

Nov 8, 2024	Our paper on PrePaMS – a privacy-preserving participant management system for studies – has been accepted for the Privacy Enhancing Technologies Symposium 2025.1.
Jun 20, 2022	I have been invited as a guest lecturer for the Reykjavík Summer School on Secure and Reliable Distributed Systems 2022 and gave a talk on Reliable Online Event Processing with Event Sourcing.
Apr 28, 2022	I have been awarded internal research start-up funding from Ulm University as part of the ProTrainU program for my work on privacy-enhanced empirical research platforms.
Jan 17, 2022	New personal website online.

Latest Publications

Article Proceedings on Pr...

PrePaMS: Privacy-Preserving Participant Management System for Studies with Rewards and Prerequisites

Meißner, Echo, Kargl, Frank, Erb, Benjamin, and Engelmann, Felix

Proceedings on Privacy Enhancing Technologies 2025

Abstract Preprint

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.
Article JMIR Mental Health

Effects of a Chatbot-Based Intervention on Stress and Health-Related Parameters in a Stressed Sample: Randomized Controlled Trial

Schillings, Christine, Meißner, Echo, Erb, Benjamin, Bendig, Eileen, Schultchen, Dana, Pollatos, Olga, and others,

JMIR Mental Health 2024

DOI WWW
Article Frontiers in Digi...

A chatbot-based intervention with ELME to improve stress and health-related parameters in a stressed sample: Study protocol of a randomised controlled trial

Schillings, Christine, Meißner, Dominik, Erb, Benjamin, Schultchen, Dana, Bendig, Eileen, and Pollatos, Olga

Frontiers in Digital Health 2023

Abstract DOI WWW

Background: Stress levels in the general population had already been increasing in recent years, and have subsequently been exacerbated by the global pandemic. One approach for innovative online-based interventions are “chatbots” – computer programs that can simulate a text-based interaction with human users via a conversational interface. Research on the efficacy of chatbot-based interventions in the context of mental health is sparse. The present study is designed to investigate the effects of a three-week chatbot-based intervention with the chatbot ELME, aiming to reduce stress and to improve various health-related parameters in a stressed sample. Methods: In this multicenter, two-armed randomised controlled trial with a parallel design, a three-week chatbot-based intervention group including two daily interactive intervention sessions via smartphone (á 10-20 min.) is compared to a treatment-as-usual control group. A total of 130 adult participants with a medium to high stress levels will be recruited in Germany. Assessments will take place pre-intervention, post-intervention (after three weeks), and follow-up (after six weeks). The primary outcome is perceived stress. Secondary outcomes include self-reported interoceptive accuracy, mindfulness, anxiety, depression, personality, emotion regulation, psychological well-being, stress mindset, intervention credibility and expectancies, affinity for technology, and attitudes towards artificial intelligence. During the intervention, participants undergo ecological momentary assessments. Furthermore, satisfaction with the intervention, the usability of the chatbot, potential negative effects of the intervention, adherence, potential dropout reasons, and open feedback questions regarding the chatbot are assessed post-intervention. Discussion: To the best of our knowledge, this is the first chatbot-based intervention addressing interoception, as well as in the context with the target variables stress and mindfulness. The design of the present study and the usability of the chatbot were successfully tested in a previous feasibility study. To counteract a low adherence of the chatbot-based intervention, a high guidance by the chatbot, short sessions, individual and flexible time points of the intervention units and the ecological momentary assessments, reminder messages, and the opportunity to postpone single units were implemented.
Springer Internat...

Defining Privacy

Kargl, Frank, Erb, Benjamin, and Bösch, Christoph

2023

DOI WWW
Conference Paper ICPE ’23

Methodology and Framework to Determine the Isolation Capabilities of Virtualisation Technologies

Volpert, Simon, Erb, Benjamin, Eisenhart, Georg, Seybold, Daniel, Wesner, Stefan, and Domaschka, Jörg

In Proceedings of the 2023 ACM/SPEC International Conference on Performance Engineering 2023

Abstract DOI WWW

The capability to isolate system resources is an essential characteristic of virtualisation technologies and is therefore important for research and industry alike. It allows the co-location of experiments and workloads, the partitioning of system resources and enables multi-tenant business models such as cloud computing. Poor isolation among tenants bears the risk of noisy-neighbour and contention effects which negatively impacts all of those use-cases. These effects describe the negative impact of one tenant onto another by utilising shared resources. Both industry and research provide many different concepts and technologies to realise isolation. Yet, the isolation capabilities of all these different approaches are not well understood; nor is there an established way to measure the quality of their isolation capabilities. Such an understanding, however, is of uttermost importance in practice to elaborately decide on a suited implementation. Hence, in this work, we present a novel methodology to measure the isolation capabilities of virtualisation technologies for system resources, that fulfils all requirements to benchmarking including reliability. It relies on an immutable approach, based on Experiment-as-Code. The complete process holistically includes everything from bare metal resource provisioning to the actual experiment enactment. The results determined by this methodology help in the decision for a virtualisation technology regarding its capability to isolate given resources. Such results are presented here as a closing example in order to validate the proposed methodology.