Welcome at the Chair of Privacy and Security
We work on all aspects of technical data protection and network and IT security. We are primarily interested in privacy, i.e. the protection of individuals against the misuse of their data.
Over the past decades, digital technologies have developed rapidly. The advent of digital transformation and the interconnectivity of all areas of life opens up a wealth of new possibilities. Autonomous networked vehicles, cloud computing, industry 4.0, virtual reality with haptic feedback, online banking or social networks are just a few keywords that are changing the way and quality of life. However, this development also brings with it a number of challenges that people often do not immediately grasp, but which may well conflict with their interests. Our research group is engaged in the development and analysis of security concepts that protect from all types of potential attackers on such systems. We are also interested in the development of technologies that promote data protection in order to protect privacy in the digital world. Finally, we develop protocols and algorithms to secure the underlying infrastructures for communication and computation.
We are part of the KASTEL Security Research Labs, as well as the excellence cluster CeTI, the Centre for Tactile Internet with Human-in-the-Loop.
Our paper Understanding Disclosure Risk in Differential Privacy with Applications to Noise Calibration and Auditing
(Patricia Guerra-Balboa, Annika Sauer, Héber H. Arcolezi, Thorsten Strufe) has been accepted for publication at VLDB 2026.
In this paper we analyze the shortcomings of existing metrics (in particular reconstruction robustness, ReRo) that are being used in Differential Privacy to assess the disclosure risks. We show that the existing bounds do not hold under realistic assumptions, reducing the usefulness of ReRo for DP calibration and auditing. We introduce a new metric, reconstruction advantage, which unifies the risk of different attacks and has tighter bounds, therefore providing better use for noise calibration and DP auditing.
Congratulations to the authors!
Link to the preprint/extended versionJulian has been invited to the podcast Nachgefragt – wissen, wie’s läuft
of KIT. In episode 26 Zwischen Datenpaketen und Detektivarbeit
he discussed with Gabi Zachmann how WiFi can work as a surveillance tool, what the negative consequences are, and how all of that fits into the bigger context of surveillance and chat control. Note that the interview was held in German.
The episode can be found on the website of KIT, and the podcast can be subscribed to by standard podcatchers, as well as on Spotify and Apple Podcasts. A version with subtitles also exists.
Have fun listening!
Episode on the KIT webseite (German)Annika Sauer has been awarded the excellence award of the Université franco-allemande Deutsch-Französische Hochschule UFA DFH. The award goes to the best graduates of the DFH. Annika did her Master's in Informatics and Computer Science at KIT and the National School of Computer Science and Applied Mathematics of Grenoble. She did her Master's Thesis on Attack Resilience in Differential Privacy under the supervision of Patricia Guerra Balboa and Héber Hwang Arcolezi.
Congratulations!
Annika's post on LinkedInThe paper The Adverse Effects of Omitting Records in Differential Privacy: How Samping and Suppression Degrade the Privacy-Utility Tradeoff
(Àlex Miranda-Pascual, Javier Parra-Arnau, Thorsten Strufe) has been accepted for publication at USENIX Security 2026!
In this paper we research how suppression of records when using Differential Privacy impacts the privacy-utility tradeoff. For this, we analyse the privacy and utility of various DP mechanisms (Laplace, Gaussian, exponential, report noisy max, DPLloyd) in combination with sampling and suppression, and find that the loss in utility caused by deleting records negates the benefit of improving the privacy parameters.
Congratulations!
Link to the preprint
