Privacy Preserving Issues in the Dynamic Internet of Things (IoT)

Convergence of critical infrastructure and data, including government and enterprise, to the dynamic Internet of Things (IoT) environment and future digital ecosystems exhibit significant challenges for privacy and identity in these interconnected domains. There are an increasing variety of devices and technologies being introduced, rendering existing security tools inadequate to deal with the dynamic scale and varying actors. The IoT is increasingly data driven with user sovereignty being essential - and actors in varying scenarios including user/customer, device, manufacturer, third party processor, etc. Therefore, flexible frameworks and diverse security requirements for such sensitive environments are needed to secure identities and authenticate IoT devices and their data, protecting privacy and integrity. In this paper we present a review of the principles, techniques and algorithms that can be adapted from other distributed computing paradigms. Said review will be used in application to the development of a collaborative decision-making framework for heterogeneous entities in a distributed domain, whilst simultaneously highlighting privacy preserving issues in the IoT. In addition, we present our trust-based privacy preserving schema using Dempster-Shafer theory of evidence. While still in its infancy, this application could help maintain a level of privacy and nonrepudiation in collaborative environments such as the IoT.