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Trustworthy Information Processing

Today's Internet can be seen as a huge data store that collects personal and sensitive data about its users. This leads to significant security and privacy risks for end users, who lose control over the data they share. Developing methods and tools to enable a secure and privacy-friendly processing of data thus constitutes a core challenge to all data-driven ecosystems and applications. In particular, the success of digitalization heavily depends on whether companies are able to gain their users' trust regarding the protection of their privacy. This research area strives to develop disruptive new frameworks for reasoning about and improving security and privacy in information processing in various settings, efficiently and at scale. In the last years, this area had a particular focus on the following topics: novel methods and tools for the algorithmic sanitization of privacy-sensitive data, in particular for genomic and medical research; new techniques for quantitatively assessing end user privacy; as well as efficient techniques for secure, verifiable computation.

Tagged Publications

Year 2021

Conference / Medium

USENIX-Security
USENIX Security Symposium

Conference / Medium

CSF
IEEE Computer Security Foundations Symposium34th IEEE Computer Security Foundations Symposium

Conference / Medium

AAAI
35th AAAI Conference on Artificial Intelligence35th AAAI Conference on Artificial Intelligence

Conference / Medium

AAAI
Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)AAAI Conference on Artificial Intelligence

Conference / Medium

WACV
IEEE Winter Conference on Applications of Computer Vision (WACV ’20)IEEE Winter Conference on Applications of Computer Vision (WACV ’20)

Year 2020

Conference / Medium

TCC
TCC 2020Theory of Cryptography - 18th International Conference