In recent years, the growing number of devices connected to the internet has increased significantly. These devices can interact with the external environment and with human beings through a wide range of sensors that, perceiving reality through the digitization of some parameters of interest, can provide an enormous amount of data. All this data is then shared on the network with other devices and with different applications and infrastructures. This dynamic and ever-changing world underlies the Internet of Things (IoT) paradigm. To date, countless applications based on IoT have been developed; think of Smart Cities, smart roads, and smart industries. This article analyzes the current architectures, technologies, protocols, and applications that characterize the paradigm.

Today’s modern vehicles are connected to a network and are considered smart objects of IoT, thanks to the capability to send and receive data from the network. One of the greatest challenges in the automotive sector is to make the vehicle secure and reliable. In fact, there are more connected instruments on a vehicle, such as the infotainment system and/or data interchange systems. Indeed, with the advent of new paradigms, such as Smart City and Smart Road, the vision of Internet of Things has evolved substantially. Today, we talk about the V2X systems in which the vehicle is strongly connected with the rest of the world. In this scenario, the main aim of all connected vehicles vendors is to provide a secure system to guarantee the safety of the drive and persons against a possible cyber-attack. So, in this paper, an embedded Intrusion Detection System (IDS) for the automotive sector is introduced. It works by adopting a two-step algorithm that provides detection of a possible cyber-attack. In the first step, the methodology provides a filter of all the messages on the Controller Area Network (CAN-Bus) thanks to the use of a spatial and temporal analysis; if a set of messages are possibly malicious, these are analyzed by a Bayesian network, which gives the probability that a given event can be classified as an attack. To evaluate the efficiency and effectiveness of our method, an experimental campaign was conducted to evaluate them, according to the classic evaluation parameters for a test’s accuracy. These results were compared with a common data set on cyber-attacks present in the literature. The first experimental results, obtained in a test scenario, seem to be interesting. The results show that our method has good correspondence in the presence of the most common cyber-attacks (DDoS, Fuzzy, Impersonating), obtaining a good score relative to the classic evaluation parameters for a test’s accuracy. These results have decreased performance when we test the system on a Free State Attack.

The cultural heritage is one of the most important resources of the territory. It represents one of the scenarios where new technologies can provide more interesting contributions. In particular, adaptive systems and related services may increase the promotion of cultural heritage. In fact, tourists can use several services able to filter the huge amount of data present on the network in order to only provide relevant information. The aim of this paper is to introduce a chatbot based on a Context-Aware System. This chatbot recommends contents and services according to tourist profiles and context. For testing the proposed architecture, a prototype was developed in order to support tourists during a visit to some cultural sites in Campania: Paestum, Pompeii and Herculaneum. The first experimental results are encouraging and show the potential of the proposed approach.

The increasing number of connected cars introduced new cyber-attacks strategies that give life to potentially devastating scenarios on everyday life. In fat, the connected cars show many vulnerabilities and are not conform to the policies defined in the AIC Model (availability, integrity and confidentiality). On the other hand, the advantages related to cars connected are very useful for implementing new innovative scenarios providing, for example, context and situation awareness in some operative scenarios. The main problem relies in the introduction of effective techniques that works in well-known framework (PC, Smartphone, …) in a real challenging environment as the automotive. In this scenario, the main parameter to consider is that of the quick ability to identify and react a possible attack. So in this paper, an embedded Intrusion Detection System for Automotive is introduced. It works adopting a Bayesian Network approach for the quick identification of malicious messages on the controller Area Network (CAN-Bus). The first experimental results, obtained in a real scenario, seems to be real interesting.