Data Verification and Privacy in IoT Architecture

Abstract

The Internet of Things (IoT) is inspired by network interconnectedness of humans, objects, and cloud services to facilitate new use cases and new business models across multiple enterprise domains. This creates the need for continuous data streaming in IoT architectures which are mainly designed following the broadcast model. As more devices communicate with each other via the Internet, it will be crucial to determine the origins of requests and responses; especially in situations where trust is paramount such as wearable IoT. It is however difficult to determine data origins in IoT ecosystems due to the inherent sporadic nature of wireless networks. Also, multiple IoT devices can be generating similar content and it is important to identify individual data sources transparently. Some previous works focus on the request perspective and employed provenance techniques to determine data sources. However, some of these solutions are not robust for a complete message and data exchanges; especially in a request-response scenario where IoT devices are involved. Thus, this paper proposes a combination of policy-based provenance and modelled the peer-to-peer IoT device communication as a graph network. Using Floyd's algorithm, we are able to determine data origins in shortest paths between interconnected IoT devices.