Machine Cloud Connectivity: a robust communication architecture for Industrial IoT

Industry 4.0 springs from the fourth industrial revolution, which is bringing innovation to fully automated and interconnected industrial production. This movement is composed of macro areas to expand the technological horizon starting from the tools used to date. The use of data, computing power and connectivity are the fundamental concepts on which the study of this thesis is based and are declined in big data, open data, Internet of Things (IoT), machine-to-machine and cloud computing for the centralization of information and its storage. Once the data has been collected, it is necessary to derive value from it in order to obtain advantages from ”machine learning”, i.e. machines that improve their performance by ”learning” from the data collected and analyzed. The advent of the Internet of Things can be seen in all respects as the greatest technological revolution of recent years, which will bring a huge amount of information into the hands of users. The latter can offer countless advantages in daily life and in the diagnostics of the production process. Industrial IoT (IIoT) enables manufacturing organizations to create a communication path through the automation pyramid, obtaining a real data stream in order to improve the machine performances. From an information security point of view, the importance of the information transmitted should not be underestimated and this also concerns an important aspect of industry 4.0. Protocols and authentication systems are constantly updated to ensure the privacy and security the customer needs. Through this thesis project, the implementation requirements will be dealt with in order to study and analyze different vendor technologies and to construct a cloud architecture. The focus is concentrated on the cybersecurity and on the information losses avoidance in order to get a robust transfer.