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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 2020

Conference / Medium

NIPS
Neural Information Processing Systems (NeurIPS)Neural Information Processing Systems (NeurIPS)

Conference / Medium

CCS
ACM SIGSAC Conference on Computer and Communications Security (CCS)ACM SIGSAC Conference on Computer and Communications Security (CCS)

Conference / Medium

CCS
ACM SIGSAC Conference on Computer and Communications Security

Conference / Medium

ICDM
Proceedings of the IEEE International Conference on Data Mining (ICDM)IEEE International Conference on Data Mining

Conference / Medium

ICDM
Proceedings of the IEEE Interational Conference on Data Mining (ICDM)IEEE International Conference on Data Mining