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You call this secure? – Investigation of security principles for analysis algorithms

February 22nd, 2022

Thesis Type
  • Bachelor
Status
Finished
Supervisor(s)
Advisor(s)
Sascha Welten
Contact
welten@dbis.rwth-aachen.de

The state-of-the-art Personal Health Train (PHT) infrastructure enables Distributed Analytics on decentralized healthcare data while complying with the data protection laws. The Train in the PHT architecture is a data analysis algorithm encapsulated in a docker container. On the other hand, a Station is an institution with privacy-sensitive data. These Stations receives the Train one by one, then executes the algorithm and finally append the local results to the Train.

The thesis aims to design principles for secure analysis containers. Besides the theoretical foundation which is part of this thesis, also a technical proof-of-concept should be developed and tested.
The proof-of-concept should be developed using CI pipelines, which automatically validate the containerised algorithm/code.
Malicious or suspicious code snippets should be detected. The objective of this thesis is to establish trust in the published analysis, which can be used in the productive Distributed Analytics infrastructure.

If you are interested in this thesis, do not hesitate to contact us via welten@dbis.rwth-aachen.de.


Prerequisites:

Understanding of Data Analysis

In-depth knowledge about CI pipelines in Gitlab

In-depth knowledge about Docker

Related Papers:

https://publications.rwth-aachen.de/record/838535

https://publications.rwth-aachen.de/record/836539

https://publications.rwth-aachen.de/record/818987