SecureIoT will integrate and deploy its security services with various IoT platforms and infrastructures in different scenarios spanning the manufacturing (Industry 4.0), ambient assisted living and connected car areas. Each of the scenarios will provide opportunities for validating different aspects of the SecureIoT predictive security mechanisms, including end-to-end security aspects, security of multi-platform services and security of IoT applications using smart objects. The use cases are therefore complementary, not only in terms of their sector, but also in terms of the deployment and use of SecureIoT.

Digital Automation in Manufacturing (Industry 4.0)

The scenario will focus on plant networks for operations and support and enterprise networks connected to IoT platforms providing support for automation and supply chain collaboration. The technical approach of the industrial IoT use case is twofold as reliability and availability of real world production must not be brought at risk. The scenario will be operated in two different use cases.

  • Threat Prediction & Data Security in Heterogeneous (multi-vendor) Automation Environments
  • Compliance in Human-in-the-Loop Scenarios


Socially Assistive Robots for Coaching & Healthcare

Nowadays, most robots and robotics platforms tend to deliver functionalities independently of other internet-connected devices. Hence, i.e. despite their pertinence and possible integration, IoT platforms and robots operate in isolation, which is a lost opportunity for a host of innovative functionalities. Security concerns are among the main barriers and concerns against the integration of IoT with smart semi-autonomous objects such as robots. In the scope of the SecureIoT socially assisted robots scenario, we will demonstrate the secure integration of LuxAI’s QT robot(s) in an environment provided by iSPRINT’s CloudCare2U (CC2U) IoT healthcare platform, which holds the promise to enhance the functionalities offered by both QT and CC2U, while offering a host of business opportunities for both companies (LuxAI, iSPRINT). CC2U integrates a wide range of sensors and wearable devices (e.g., fibits, motion trackers) in order to accurate detect the users’ context and provide relevant personalized services. CC2U includes already a virtual robot as an output interface. As part of the scenario QT will become CC2U’s interface for interaction with end-users.

  • Data Accuracy & Theft: Blackmailing, Espionage, etc.
  • Destruction of Environment: physical damage to the robots’ environment and psychological damage to human


Connected Cars & Autonomous Driving

The automotive industry is on the cusp of the transition to automated driving. Already connected car services are available to consumers and these are increasingly providing the differentiating features driving consumer choice. It is anticipated that the connected vehicle service features deployement will increase dramatically over the coming years and with this comes the risk of malicious exploitation of the technology. This scenario within the project will focus on the implementation of secure end-to-end communications between the cloud and an automotive dedicated IoT device making use of the SecureIoT architecture and services. This device has been designed as a tool for the development of connected and automated driving.

The use cases that have been chosen and will be demonstrated are:

  • Usage Based Insurance
  • Warnings on Traffic and Road Conditions