P2F: A User-Centric Privacy Protection Framework

In this paper, we present an end-user tool called the Privacy Protection Framework (P2F) which aims to support users in protecting their privacy when obtaining web-based services. P2F acts as a recommendation tool that analyzes the user's transaction history and privacy preferences in addition to real-world privacy privacy guidelines to prevent undesirable disclosure of personal data. The framework is based on a novel qualitative privacy compromise risk assessment approach designed to support decision-making in settings where server-side support for user-centric privacy protection frameworks is minimal or unkown. Our risk assessment model uses service provider properties, likelihood of collusion between providers, the sensitivity of the personal data to be released, and undesirable transaction linkability to determine the privacy compromise potential of a transaction.