User modelling for privacy-aware self-disclosure

Information and Communications Technology (ICT) is proliferating exponentially and has undoubtedly become an intrinsic part of our daily lives. However, its fast-paced growth has brought upon multiple challenges amongst which are the human-centric threats to cybersecurity and privacy. One of the main reasons for this is the shift in individuals’ behaviour towards carelessly disclosing private information, especially on social media.This work builds on the existing literature that identifies the motivations leading to oversharing in order to predict and mitigate self-disclosure. This paper aims to tackle this first by proposing a user model for the individual’s disclosure motivations. The aim is to measure how driven the user is to share personal information given a specific context. This is paramount to second objective, which is designing personalized privacy-preserving interventions known as nudges based on the user model. A visual aid is provided to further attract the user’s attention and persuade them to alter their behaviour. Study participants (N=800) were recruited via Mechanical Turk and responded to realistic scenarios to assess their motivations for sharing personal data. Then, persuasive nudges were pushed in the context of the evaluation.