The thesis takes this all-important question further down, into the realms of Generative AI (GenAI) platforms — a landscape that is swiftly changing yet already old enough to bring along tons and tons of interesting privacy security challenges alongside. While the onset of these advanced GenAI technologies allows for increasingly sophisticated productions across texts, images, music, and practically all types of data there is a growing concern about how to protect personal or confidential information. These platforms have been rapidly adopted more broadly, and as a result, it is increasingly important to consider the implications of how data are used, stored, and protected — especially given the size of datasets needed for training these models.