Information Systems Engineering

Privacy Engineering

In the light of omnipresent digitization, privacy challenges become increasingly prominent. Privacy Engineering is an emerging field of research and practice that takes the more „traditional“ security research to the level of practically applicable, proven solutions in businesses and society.

Privacy Engineering considers all privacy principles and requirements, including  anonymity and security but also purpose limitation and transparency. Privacy Engineering explicitly goes beyond foundational algorithms and cryptographic primitives and prominently addresses factors such as technical system environments, organizational embedding, actual legal/regulatory givens and corresponding questions of legal/regulatory compliance, and human factors when designing novel or assessing existing privacy mechanisms for real-world use cases.

In our Privacy Engineering research, we consciously go the extra mile towards actual applicability in real-world, enterprise-grade distributed software systems and take respective challenges into account as equally relevant research subjects. This particularly includes the experimental assessment of nonfunctional properties of privacy and security mechanisms (performance impacts, scalability, load-specific effects, …), thereby fostering evidence-based trade-offs – for instance between security and performance or between anonymity level and remaining data utility.

Together with further consideration of other  non-functional properties such as (re-) usability in relevant real-world software systems contexts, coherent integration into established software stacks, architectures and development practices, or developer-friendliness, this allows us to make path-breaking contributions to the field of Privacy Engineering or, as others denote it, Privacy by Design (PbD). In particular, we develop paradigmatically novel approaches with dedicated practical relevance in areas such as novel access control schemes and mechanisms, transparency and accountability technologies, or the quality- and performance-aware provision of anonymity guarantees. 

Our concepts (and the respective prototypes) are specifically tailored to and proven to be applicable in industry-grade distributed software systems and architectures. We thereby significantly advance the state of the art in Privacy Engineering, allowing industry to better materialize privacy requirements in real-world technologies. We educate the next-generation of Privacy Engineers, a specialization and skill that has been denoted the “superheroes” discipline within the privacy profession.

Related Projects

Current Projects

Finished Projects



Related Publications


Grünewald, Elias; Kiesel, Jannis; Loechel, Louis; Janke, Thomas; Akbayin, Siar-Remzi
Advancing Transparency Enhancing Tools for Cloud-Native Architectures and Engineering
Forum Privatheit 2023
Publisher: Forum Privatheit
October 2023
Gebauer, Michael; Maschhur, Faraz; Leschke, Nicola; Grünewald, Elias; Pallas, Frank
A ‘Human-in-the-Loop’ Approach for Information Extraction from Privacy Policies under Data Scarcity
2023 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW), Page 76-83
Publisher: IEEE Computer Society, Los Alamitos, CA, USA
July 2023
Grünewald, Elias; Halkenhäußer, Johannes M.; Leschke, Nicola; Washington, Johanna; Paupini, Cristina; Pallas, Frank
Enabling Versatile Privacy Interfaces Using Machine-Readable Transparency Information
In Schiffner, Stefan and Rodriguez, Adrian Quesada and Ziegler, Sebastien, Editor, Privacy Symposium 2023
In Schiffner, Stefan and Rodriguez, Adrian Quesada and Ziegler, Sebastien, Editor
Publisher: Springer International Publishing
Grünewald, Elias; Kiesel, Jannis; Akbayin, Siar-Remzi; Pallas, Frank
Hawk: DevOps-driven Transparency and Accountability in Cloud Native Systems
2023 IEEE 16th International Conference on Cloud Computing (CLOUD), Page 167–174
Publisher: IEEE
Leschke, Nicola; Kirsten, Florian; Pallas, Frank; Grünewald, Elias
Streamlining personal data access requests: From obstructive procedures to automated web workflows
In Garrigós, Irene and Murillo Rodríguez, Juan Manuel and Wimmer, Manuel, Editor, Web Engineering. ICWE 2023Volume13893fromLecture Notes in Computer Science, Page 111–125
In Garrigós, Irene and Murillo Rodríguez, Juan Manuel and Wimmer, Manuel, Editor
Publisher: Springer, Cham
Plebani, Pierluigi; Kat, Ronen; Pallas, Frank; Werner, Sebastian; Inches, Giacomo; Laud, Peeter; Santiago, Rita
TEADAL: Trustworthy, Energy-Aware federated DAta Lakes along the computing continuum
Grünewald, Elias; Halkenhäußer, Johannes M.; Leschke, Nicola; Pallas, Frank
Towards Cross-Provider Analysis of Transparency Information for Data Protection
Publisher: under review
Sedlak, Boris; Pujol, Victor Casamayor; Donta, Praveen Kumar; Werner, Sebastian; Wolf, Karl; Falconi, Matteo; Pallas, Frank; Dustdar, Schahram; Tai, Stefan; Plebani, Pierluigi
Towards Serverless Data Exchange Within Federations
In Aiello, Marco and Barzen, Johanna and Dustdar, Schahram and Leymann, Frank, Editor, Service-Oriented Computing, Page 144-153
In Aiello, Marco and Barzen, Johanna and Dustdar, Schahram and Leymann, Frank, Editor
Publisher: Springer Nature Switzerland


Heiss, Jonathan; Grünewald, Elias; Tai, Stefan; Haimerl, Nikolas; Schulte, Stefan
Advancing Blockchain-based Federated Learning through Verifiable Off-chain Computations
2022 IEEE International Conference on Blockchain (Blockchain), Page 194–201
Grünewald, Elias
Cloud Native Privacy Engineering through DevPrivOps
Privacy and Identity Management. IFIP International Summer School, Esch-sur-Alzette, 2021
Publisher: Springer International Publishing, Cham