End-to-End Privacy for Open Big Data Markets
Charith Perera, Rajiv Ranjan, Lizhe Wang

TL;DR
This paper discusses the importance of privacy in IoT open data markets, surveys existing privacy-preserving strategies, and highlights research challenges to enable secure data trading.
Contribution
It provides a comprehensive survey of privacy techniques for open IoT data markets and identifies key research challenges for future solutions.
Findings
Privacy is critical in IoT data markets due to sensitive personal information.
Existing privacy-preserving strategies include encryption, anonymization, and access control.
Major research challenges involve balancing data utility with privacy and developing scalable solutions.
Abstract
The idea of an open data market envisions 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 behaviours of data owners and to generate additional business value using different 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…
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