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The emerging Internet of Things (IoT) leads to a dramatic increase in type, quantity, and the number of functions that it can perform in a smart environment. Future smart environments will be even more abundant in terms of the number of devices and functionality that they can provide. This poses two main challenges for end users when automating their activities; a) they have to search through a vast number of IoT devices to identify the suitable devices that satisfy their preferences; and b) it is extremely difficult for users to define fine-grained security policies to support activities workflows. This paper introduces a new intelligent approach to overcome these challenges by a) enabling users to describe their required functionalities in the form of activity workflow; b) automatically selecting a group of devices to satisfy users functional requirements and maximise their preferences over device usage; c) systematically generating local network access control policies to ensure enforce the principle of least privilege. We study different heuristic search algorithms to find the preferred devices for a given workflow. Experiments results show that the Genetic Algorithm is the best, among the algorithms that we test, as it offers a balance between efficiency and effectiveness.

2019 18th ieee international conference on trust, security and privacy in computing and communications/13th ieee international conference on big data science and engineering (trustcom/bigdatase)

Automatic Device Selection and Access Policy Generation Based on User Preference for IoT Activity Workflow