Recently established in our new environment in Salzburg, we are currently looking for new national and international project opportunities as well as other collaborations with partners from research and industry. Interested in joint activities along our lines of research? Get in touch!

Current projects

EXDIGIT

Excellence in Digital Sciences and Interdisciplinary Technologies

In 2022, the Paris Lodron University of Salzburg (PLUS) established the new Faculty of Digital and Analytical Sciences (DAS). The EXDIGIT project aims to establish this newly founded faculty as an interdisciplinary research platform with critical mass and international visibility in the aforementioned digital topics. The PEPSys @ PLUS group is one piece within this initiative, along the “sibling” groups for Interactive Intelligent Systems and Space and Place in the Information Sciences as well as many further activities.

Past Projects

Before joining PEPSys @ PLUS, our team members were involved in the following projects at TU Berlin’s Information Systems Engineering group (in chronological order, covering projects since 2017):

GANGES

Assurance of Anonymity Guarantees in Enterprise Streaming-Applications (Gewährleistung von Anonymitäts-Garantien in Enterprise-Streaminganwendungen)

Assuring anonymity guarantees is crucial for the implementation of novel, data-driven applications, and business models. Basic models and techniques such as k-anonymity or differential privacy already exist but are barely used in practice. This can be attributed to a lack of support for complex data types as particularly relevant in real-world applications as well as to insufficient addressing of communication and architectural models as broadly used in enterprise environments and usecases – especially regarding the paradigm of stream processing. Through consequent integration of the three aspects “anonymity”, “data utility” and “integrability / overheads”, the project provides important contributions to the concrete applicability of modern anonymization techniques and, thus, to the actual practicability of novel, data-driven applications and business models.

TEADAL

Trustworthy, Energy-Aware Federated Data Lakes Along the Computing Continuum

The so-called Cloud-Edge Continuum, which enables the operation and management of data both close to in-field sensors as the data sources (the edge) and in remote cloud data lakes in the backend, provides initial answers to address availability and performance issues in modern, data-driven and data-heavy applications. TEADAL addresses issues such as confidentiality and trustworthiness of data within respective settings and, in particular, beyond the organizational context while also taking questions of energy-efficiency into account.

Gaia-X 4 PLC-AAD

Gaia-X for Product Lifecycle Across Automated Driving

The development of automated driving functions is becoming increasingly complex and costly due to the required combination of software and hardware and their safeguarding. At the same time, OEMs and suppliers are facing ever new challenges in the design of their supply chains. In both cases, improvements require bringing together large amounts of data from different sources. Gaia-X 4 PLC-AAD aims to develop and construct an open data ecosystem in environments for automated driving that enables the efficient exchange of data and services while also ensuring the necessary security at the technical level.

DaSKITA

Data Sovereignty Through AI-based Transparency and Access (Datensouveränität durch KI-basierte Transparenz und Auskunft (DaSKITA))

The aim of this project was the design and prototypical implementation of AI-based concepts, mechanisms and tools which enable consumers to obtain a higher level of awareness and self-determination in the context of data-driven services. Transparency and the right of access have always been an integral part of privacy / data-protection regulations: to be able to act in a sovereign and self-determined way in everyday digital life, consumers need to know ‘who knows what, when, and on what occasion about them’ (BVerfG 1983, RN 94). In close cooperation between computer science, legal and socio-political research as well as corporate practice, AI-based technologies for the low-effort exercise of transparency and access rights, for simplified reception of appropriate information and its machine-readable provision by service providers were to be developed in this project.

EMIDD

Consent Management for the Internet of Things (Einwilligungsmanagement für das internet der Dinge)

Individual, informed, specific and explicitly given consent is one of the main pillars of data protection law. Traditionally, such consent has been given, for example, in writing or by ticking a box under a privacy statement several pages long. In the context of the IoT - where, on the one hand, traditional user interfaces are not available and, on the other, data once collected can be used for a variety of other desirable purposes - this approach is obviously no longer viable. Instead, new, technically supported approaches to consent management are needed. In the EMIDD project, possibilities of such technical approaches as well as their connectivity to current and future data protection law were being researched, including the design, prototypical implementation, and evaluation of respective mechanisms.

  • Website: https://github.com/EMIDD-Projekt
  • Partners: iRights.Lab
  • Overall Funding: 100k €
  • Funded by: Federal ministry of Justice and for Consumer Protection (BMJV, DE)
  • Project duration: 04/2017 - 06/2018
  • Involved PEPSys members and role: Frank Pallas (PI and overall project lead)

DITAS

Data-intensive Applications Improvement by moving Data and Computation in mixed Cloud/Fog Environments

New data intensive applications such as autonomous driving, e-health or industry 4.0 require faster response times and stronger privacy and security guarantees than current cloud providers can offer. Fog computing is one way to address these requirements but also introduces new challenges in matters such as security or privacy. DITAS envisioned, designed and prototypically implemented a respective cloud-edge data management system that is aware of resource limitations of edge locations and helps to synchronize data between cloud and edge while still complying with privacy and security requirements. On this basis, information in the e-health context, for instance, can only be shared with research institutions, and only after the data was anonymized and the patients gave their explicit agreement to share their data.