<p dir="ltr">In this era of digital surveillance and data breaches, it is important to understand how users protect their smartphone privacy. There needs to be more detailed information regarding the prevalence, factors, and motivations influencing the adoption of privacy-enhancing tools and settings on mobile devices. This study aimed to address this knowledge gap by investigating the use of privacy tools among smartphone users and examining the impact of factors like demographics, awareness levels, and device platforms.</p><p dir="ltr">The study surveyed 342 participants recruited through Amazon Mechanical Turk (MTurk), and the data were analyzed. The survey gathered data on user characteristics, privacy concerns, experiences with breaches, and use of various privacy tools. Statistical analysis showed that demographic factors, particularly age, significantly influenced the use of privacy tools, aligning with previous research. Users with a higher awareness of digital privacy risks were likelier to adopt privacy-enhancing tools. The study found no significant difference in the prevalence and type of privacy tools used between iOS and Android users.</p><p dir="ltr">The study's focus on privacy-enhancing tools among smartphone users and the proposed hypotheses provide valuable insights for law enforcement and forensic practitioners, aiding in digital investigations, evidence collection, and understanding user behavior related to smartphone privacy measures. The study's outcomes contribute to digital forensics, cybersecurity, and privacy domains by providing insights into user behaviors, motivations, and the factors shaping privacy tool adoption on smartphones. These findings can inform the development of more user-centric privacy tools, policies, and educational campaigns, ultimately enhancing digital privacy protection and supporting law enforcement investigations in the digital age.</p>

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.

In this research end user privacy preferences regarding online resources web and mobile applications and websites are investigated and design requirements needed for the development of a privacy focused, privacy enhancing technology tool are identified, as derived from the literature, the crowd source based solution is the most appealing solution so it is fully analyzed according to our research main focus.

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.