Privacy Knowledge Modelling for Internet of Things: A Look Back

TL;DR

This paper reviews how privacy knowledge has been modeled across various domains, analyzing past research to understand its application and challenges in IoT privacy management.

Contribution

It provides a comprehensive analysis and comparison of existing privacy knowledge models, highlighting their relevance and challenges for IoT privacy.

Findings

Privacy models vary across domains and have different strengths.

Understanding stakeholder privacy expectations is crucial for IoT.

Future research should address identified challenges and opportunities.

Abstract

Internet of Things (IoT) and cloud computing together give us the ability to sense, collect, process, and analyse data so we can use them to better understand behaviours, habits, preferences and life patterns of users and lead them to consume resources more efficiently. In such knowledge discovery activities, privacy becomes a significant challenge due to the extremely personal nature of the knowledge that can be derived from the data and the potential risks involved. Therefore, understanding the privacy expectations and preferences of stakeholders is an important task in the IoT domain. In this paper, we review how privacy knowledge has been modelled and used in the past in different domains. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT. Finally, we discuss major research challenges and opportunities.