E5 – Privacy-Aware Distributed Computation
The project addresses the challenge of automated generation of scalable privacy-preserving mechanisms in IoT, cloud, and edge computing systems. The project designs SecQL, a query language for data-intensive applications, whose runtime environment automatically generates and deploys sub-computations over nodes of the above systems to optimize performance while protecting the processed data from unauthorized access. The formally defined SecQL makes privacy-preserving mechanisms accessible also for non-security experts.
Researchers
Mirko Köhler
Reactive Software Systems
Research Interests:
- Programming languages for distributed systems
Publications
Köhler, Mirco ; Salvaneschi, Guido (2019):
Automated Refactoring to Reactive Programming.
In: ASE'19 - The 34th International Conference on Automated Software Engineering, San Diego, Ca, USA, November 10.-15.,2019, DOI: 10.1109/ASE.2019.00082,
[Online-Edition: https://2019.ase-conferences.org/],
[Konferenzveröffentlichung]
Salvaneschi, Guido ; Köhler, Mirko ; Sokolowski, Daniel ; Haller, Philipp ; Erdweg, Sebastian ; Mezini, Mira (2019):
Language-integrated privacy-aware distributed queries.
3, In: Proceedings of the ACM on Programming Languages, 2019, (OOPSLA), ACM, S. 167, ISSN 2475-1421, DOI: 10.1145/3360593,
[Online-Edition: https://dl.acm.org/citation.cfm?id=3360593],
[Article]
Schulz, Philipp (2019):
Developing Secure Distributed Systems with Modular Tierless Programming.
TU Darmstadt, [Masterarbeit]
Srivatsa, Jeevan Karanam (2019):
Benchmarking of Data Provenance Computation Methods to Support Debugging in Apache Spark.
TU Darmstadt, [Masterarbeit]
Oak, Aditya ; Mezini, Mira ; Salvaneschi, Guido (2019):
Language Support for Multiple Privacy Enhancing Technologies.
ACM, In: Conference Companion of the 3rd International Conference on Art, Science, and Engineering of Programming, [Konferenzveröffentlichung]