During her PhD studies, Hannah Keller studied privacy in distributed environments for a variety of data analytics tasks. Her research focuses on differential privacy in combination with secret sharing techniques, which together enable a group of mutually distrusting individuals to compute a function of their joint inputs in such a way that the output does not reveal too much about any single individual. Her work provides private, efficient algorithms and protocols for summation, low-rank approximation, regularized linear regression, selection, and quantile computation. These works provide useful trade-offs between accuracy, privacy guarantees, computation, and communication.

The PhD study was completed at the Department of Computer Science, Faculty of Natural Sciences, Aarhus University.

This summary was prepared by the PhD student.

Time: Friday, 20 February 2025 at 12:30
Place: Building 5342, room 333, Department of Computer Science, Aarhus University, Åbogade 34, 8200 Aarhus
Title of PhD thesis: Distributed Differential Privacy Using Cryptographic Techniques
Contact information: Hannah Keller, e-mail: hkeller@cs.au.dk
Members of the assessment committee:
Associate Professor Varun Kanade, Computer Science, Oxford University, United Kingdom
Principal Researcher Divya Gupta, Microsoft Research Lab, India
Associate Professor Sophia Yakoubov (chair), Department of Computer Science, Aarhus University, Denmark
Main supervisor: Professor Claudio Orlandi, Department of Computer Science, Aarhus University, Denmark
Co-supervisor: Associate Professor Chris Schwiegelshohn, Department of Computer Science, Aarhus University, Denmark
Language: The PhD dissertation will be defended in English

The defense is public.
The PhD thesis is available for reading at the Graduate School of Natural Sciences/GSNS, Ny Munkegade 120, building 1521, 8000 Aarhus C