Privacy Enhancing Technologies E192-08
The rapid growth in data collection, fueled by digitization and the rise of connected devices, is creating exciting opportunities for innovation and greater efficiency across many domains. However, this surge in data also brings new risks, including increased vulnerability to cyberattacks and emerging privacy concerns, especially as advances in Artificial Intelligence enable the processing of vast amounts of personal data.
Contact
- Head: Dominique Schröder
- Web: informatics.tuwien.ac.at/orgs/e192-08
- Location: Erzherzog-Johann-Platz 1
On This Page
About
The rapid growth in data collection, fueled by digitization and the rise of connected devices, is creating exciting opportunities for innovation and greater efficiency across many domains. However, this surge in data also brings new risks, including increased vulnerability to cyberattacks and emerging privacy concerns, especially as advances in Artificial Intelligence enable the processing of vast amounts of personal data.
To address these challenges, our Research Unit is dedicated to reconciling technological progress with the protection of users’ privacy. We are pioneering the development of state-of-the-art cryptographic techniques and advanced privacy-enhancing tools. These tools ensure that innovation in areas such as distributed systems, cryptocurrencies, smart healthcare, and smart cities can continue to thrive without sacrificing personal privacy.
Using sophisticated methods such as secure multi-party computation, homomorphic encryption, and differential privacy, we demonstrate that it is possible to preserve privacy while driving technological progress at the same time. Our work underscores the possibility of a future where privacy and innovation are not mutually exclusive but can coexist harmoniously.
The research Unit Privacy Enhancing Technologies is part of the Institute of Logic and Computation.
Professors
Scientific Staff
Courses
2024W
- Bachelor Thesis / 192.145 / PR
- Privacy-Enhancing Technologies / 192.144 / VU
- Project in Computer Science 1 / 192.021 / PR
- Project in Computer Science 2 / 192.022 / PR
- Seminar for PhD Students / 192.146 / SE
Publications
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Measuring Conditional Anonymity - A Global Study
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Berrang, P., Gerhart, P. C., & Schröder, D. (2024). Measuring Conditional Anonymity - A Global Study. Proceedings on Privacy Enhancing Technologies (PoPETs), 2024(4), 947–966. https://doi.org/10.56553/popets-2024-0150
Download: PDF (5.7 MB)
And more…
Soon, this page will include additional information such as reference projects, conferences, events, and other research activities.
Until then, please visit Privacy Enhancing Technologies’ research profile in TISS .