End-to-end privacy for open big data markets

Abstract

Establishing an open data market would require the creation of a data trading model to facilitate exchange of data between different parties in the Internet of Things (IoT) domain. The data collected by IoT products and solutions are expected to be traded in these markets. Data owners will collect data using IoT products and solutions. Data consumers who are interested will negotiate with the data owners to get access to such data. Data captured by IoT products will allow data consumers to further understand the preferences and behaviors of data owners and to generate additional business value using techniques ranging from waste reduction to personalized service offerings. In open data markets, data consumers will be able to give back part of the additional value generated to the data owners. However, privacy becomes a significant issue when data that can be used to derive extremely personal information is being traded. This article discusses why privacy matters in the IoT domain in general and especially in open data markets, and then surveys existing privacy-preserving strategies and design techniques that can be used to facilitate end-to-end privacy for open data markets. It also highlights some of the major research challenges that must be addressed to make the vision of open data markets a reality through ensuring the privacy of stakeholders. Show more