Trustworthy People-Centric Sensing: Privacy, security and user incentives road-map
Thanassis Giannetsos, Stylianos Gisdakis, Panos Papadimitratos · 2014
The broad capabilities of widespread mobile devices have paved the way for People-Centric Sensing (PCS). This emerging paradigm enables direct user involvement in possibly large-scale and diverse data collection and sharing. Unavoidably, this raises significant privacy concerns, as participants may inadvertently reveal a great deal of sensitive information. However, ensuring user privacy, e.g., by anonymizing data they contribute, may cloak faulty (possibly malicious) actions. Thus, PCS systems must not only be privacy-preserving but also accountable and reliable. As an increasing number of applications (e.g., assistive healthcare and public safety systems) can significantly benefit from people-centric sensing, it becomes imperative to meet these seemingly contradicting requirements. In this work, we discuss security, user privacy and incentivization for this sensing paradigm, exploring how to address all aspects of this multifaceted problem. We critically survey the security and privacy properties of state-of-the-art research efforts in the area. Based on our findings, we posit open issues and challenges, and discuss possible ways to address them, so that security and privacy do not hinder the deployment of PCS systems.