The subject of this dissertation is the construction of privacy-enhancing technologies (PETs) for transparency logging, a technology at the intersection of privacy, transparency, and accountability. Transparency logging facilitates the transportation of data from service providers to users of services and is therefore a key enabler for ex-post transparency-enhancing tools (TETs). Ex-post transparency provides information to users about how their personal data have been processed by service providers, and is a prerequisite for accountability: you cannot hold a controller accountable for what is unknown. We present three generations of PETs for transparency logging to which we contributed. We start with early work that defined the setting as a foundation and build upon it to increase both the privacy protections and the utility of the data sent through transparency logging. Our contributions include the first provably secure privacy-preserving transparency logging scheme and a forward-secure append-only persistent authenticated data structure tailored to the transparency logging setting. Applications of our work range from notifications and deriving data disclosures for the Data Track tool (an ex-post TET) to secure evidence storage. / The subject of this dissertation is the construction of privacy-enhancing technologies (PETs) for transparency logging, a technology at the intersection of privacy, transparency, and accountability. Transparency logging facilitates the transportation of data from service providers to users of services and is therefore a key enabler for ex-post transparency-enhancing tools (TETs). Ex-post transparency provides information to users about how their personal data have been processed by service providers, and is a prerequisite for accountability: you cannot hold a controller accountable for what is unknown. We present three generations of PETs for transparency logging to which we contributed. We start with early work that defined the setting as a foundation and build upon it to increase both the privacy protections and the utility of the data sent through transparency logging. Our contributions include the first provably secure privacy-preserving transparency logging scheme and a forward-secure append-only persistent authenticated data structure tailored to the transparency logging setting. Applications of our work range from notifications and deriving data disclosures for the Data Track tool (an ex-post TET) to secure evidence storage.

Medical researchers are exploring the potential of patients’ mobile phones and wearables for medical studies. The contribution of volunteers in a form of citizen science, where citizens donate their data for research purposes, can enable studies on a large scale. This research area, known as mobile health, often relies on shared data such as tracked steps or self- reporting forms. Privacy, transparency and trust play a fundamental role in the interaction of users with related platforms that agglomerate medical studies.This project explores privacy concerns of potential users of mobile health citizen science apps, summarises similar user patterns and analyses the impact of transparency enhancing tools on the users’ trust. In this context, a prototype with different features that aim to increase the transparency is designed, tested and evaluated. The results indicate how users perceive the importance and the generated trust of the proposed features and provide recommendations for data donation platforms.