An Ambient Intelligence approach to provide secure and trusted Pub/Sub messaging systems in IoT environments

Abstract

[EN] Ambient Intelligence (AmI) is defined as a high-quality vision technology where content and information can be sensed and adopted from anytime, anywhere, and by any user in the environment. Much of the research in this area has focused on several aspects of AmI, such as computational and storage complexity, accuracy, and transmission criteria. However, few works have focused on the various trust and security concerns associated to the message publish/subscribe (Pub/Sub) procedure when the on-the-fly technique is adopted. In fact, malicious devices may easily breach the legitimate devices with the aim of degrading the security and privacy in the network. The aim of this paper is to propose a secure and trusted on-the-fly Pub/Sub communication mechanism where the trust and transmission among various devices occurs by computing their trust using indirect factors. In addition, the accuracy and legitimacy of each communicating device is validated using a reinforcement learning scheme. Moreover, the proposed solution is validated and verified against various security measures over a traditional approach.