From Data Disclosure to Privacy Nudges: A Privacy-aware and User-centric Personal Data Management Framework

TL;DR

This paper introduces a user-centric framework for personal data management that assesses privacy risks and benefits, enabling personalized privacy protection through nudges and continuous monitoring.

Contribution

It presents a novel conceptual framework combining privacy risk assessment with value evaluation, incorporating human-in-the-loop and preference learning for personalized privacy control.

Findings

Framework can assess privacy risks and benefits simultaneously

Personalized privacy nudges are feasible through continuous monitoring

Case study demonstrates applicability to leisure travelers

Abstract

Although there are privacy-enhancing tools designed to protect users' online privacy, it is surprising to see a lack of user-centric solutions allowing privacy control based on the joint assessment of privacy risks and benefits, due to data disclosure to multiple platforms. In this paper, we propose a conceptual framework to fill the gap: aiming at the user-centric privacy protection, we show the framework can not only assess privacy risks in using online services but also the added values earned from data disclosure. Through following a human-in-the-loop approach, it is expected the framework provides a personalized solution via preference learning, continuous privacy assessment, behavior monitoring and nudging. Finally, we describe a case study towards "leisure travelers" and several future areas to be studied in the ongoing project.