There are major discussions about the vulnerability of protocols based on Real Time Ethernet (RTE) and techniques for detecting anomalies. Thus, this work proposes a methodology for detecting anomalies by optimizing the data extraction and by classifying traffic-related features. In order to cope with this proposal, an ANN-based classifier is trained using selected relevant features. These features are extracted using variable sized sliding window and selected according to their correlation with the other features and the expected output of the ANN. The number of relevant features can vary according to performance indicators of the classifier. The proposed methodology was exploited for identifying four different events of PROFINET networks and the performance of the classifier was considered successful for all cases. This outcome suggests that the proposed methodology may be successful for anomalies detection in any PROFINET network. However, the application of the proposed methodology to other RTE protocol is foreseen.

The Internet of Things (IoT) is a key technology in the development of Industry 4.0. An increasing number of new industrial devices are expected to communicate with each other by means of local (edge) and cloud computing servers. In this article, two well-known protocols used for IoT and Industrial IoT (IIoT) are compared in terms of their performance when they are used to send/receive data to/from cloud servers. Due to their wide diffusion and suitability, the considered protocols are open platform communication-unified architecture publisher-subscriber (OPC UA PubSub) (purposely developed and maintained by industrial consortia) and message queuing telemetry transport (MQTT), the most well-known message protocol originally developed by IBM. The performance comparison is carried out considering the overall quantity of the data transferred (user payload plus overhead) and the roundtrip time required to send in data and receive a feedback message in return. The experimental results include the evaluation of several cloud computing server and application scenarios, highlighting how each protocol is particularly suitable for certain situations. Finally, conclusions about the best choice for data exchange between devices are given.

With the new concepts brought by the Industry 4.0 and the Internet of Things (IoT), it is expected more equipment communicating with each other, using local and cloud computing servers. In order to the communication between the devices be efficient, fast and with time deterministic, it is necessary to choose a suitable network protocol. In this context, the article presents the performance comparison of quantity of used data and time spent to send and receive messages in two well-known protocols in the field of IoT and Industrial loT (IIoT): MQTT and OPC UA. The obtained values show the advantages of using each protocol in several scenarios, in order to exploit the best data exchange between devices.

Currently, in a scenario of Industry 4.0, the communication protocol is a key factor of success for modern industry. Allits needs could be fulfilled by Ethernet based protocols. One of the most used protocols is PROFINET{concerning the number of applications in growth in the last years, being one of the most promising protocols for the future. Considering its importance, this paper discusses a panorama which characterize the current scenario of this protocol. To achieve the main goals, 92 studies were considered in the data extraction. The obtained results were relevant to provide a current panorama of the area, as well as outlines a number of possible research directions, challenges and opportunities in PROFINET technology research such as diagnostics and security.