Data-centric framework for adaptive smart city honeynets

Abstract

A smart city system will contain diverse heterogeneous smart objects. Their complexity will range from simple reduced function devices (RFD) acting as common nodes, to full function devices (FFD) acting as coordinators and controlling actuators. As part of the Internet of Things, web facing devices can be remotely accessed for monitoring, control and data exchange. This makes them vulnerable to cyber attacks and compromise. To analyse such attacks, honeynets and honeypots are deployed to attract attackers and capture their activity for behavioural analysis. Designing honeynets is difficult due to the broad engineering scope of smart cities as a concept, and consequent diversity of smart object characteristics such as communication channels, interaction, data exchange and embedded security. This paper brings order to this diversity and scope by taking a data-centric view of smart city devices. The data-centric view assesses smart devices for their criticality, security and complexity. It presents a framework using this view, for adaptive honeynet development. It then validates the new framework by categorizing smart objects using the data centric view and applying them to the framework.