The use of Radio Frequency Identification technology (RFID) in medical context enables not only drug identification, but also a rapid and precise identification of patients, physicians, nurses or any other health caregiver. The combination of RFID tag identification with structured and secured Internet of Things (IoT) solutions enables ubiquitous and easy access to medical related records, while providing control and security to all interactions. This paper defines a basic security architecture, easily deployable on mobile platforms, which would allow to establish and manage a medication prescription service in mobility context making use of electronic Personal Health Records. This security architecture is aimed to be used with a mobile e-health application (m-health) through a simple and intuitive interface, supported by RFID technology. This architecture, able to support secured and authenticated interactions, will enable an easy deployment of m-health applications. The special case of drug administration and ubiquitous medication control system, along with the corresponding Internet of Things context, is presented. The security architecture and its protocols, along with a general Ambient Assisted Living secure service for medication control, is then analyzed in the context of the Internet of Things.

Vehicular Ad hoc Networks (VANETs) are an emerging type of network that increasingly encompass a larger number of vehicles. They are the basic support for Intelligent Transportation Systems (ITS) and for establishing frameworks which enable communication among road entities and foster the development of new applications and services aimed at enhancing driving experience and increasing road safety. However, VANETs’ demanding characteristics make it difficult to implement security mechanisms, creating vulnerabilities easily explored by attackers. The main goal of this work is to propose an Intelligent Hierarchical Security Framework for VANET making use of Machine Learning (ML) algorithms to enhance attack detection, and to define methods for secure communications among entities, assuring strong authentication, privacy, and anonymity. The ML algorithms used in this framework have been trained and tested using vehicle communications datasets, which have been made publicly available, thus providing easily reproducible and verifiable results. The obtained results show that the proposed Intrusion Detection System (IDS) framework is able to detect attacks accurately, with a low False Positive Rate (FPR). Furthermore, results show that the framework can benefit from using different types of algorithms at different hierarchical levels, selecting light and fast processing algorithms in the lower levels, at the cost of accuracy, and using more precise, accurate, and complex algorithms in nodes higher in the hierarchy.

Smart cities are an ongoing research topic with multiple sub-research areas, from traffic control to optimization and even safety. However, testing the new methodologies or technologies directly in the real world is an almost impossible feat that, inclusively, can result in disaster. Thus, there is the importance of simulation. Simulation enables testing new and complex methodologies and gauging their impact in a realistic context without adding any safety issues. Additionally, these can accurately map real-world conditions depending on the simulation configuration. One key aspect of the simulation is the traffic flows in the simulated region. These may be hard to find and, if ill-set, may introduce bias in the results. This work is on the characterization of the traffic in the city center of Guimarães, Portugal. An urban simulation scenario was established, using SUMO as the mobility traffic simulator, with traffic patterns derived from real-world data provided by Guimarães City Hall and using Eclipse MOSAIC for extended vehicular simulation. Apart from mobility patterns analysis, this work also provides publicly accessible datasets, simulations, and applications made available to future research works.

It is expected in a near future that safety applications based on vehicle-to-everything communications will be a common reality in the traffic roads. This technology will contribute to improve the safety of vulnerable road users, for example, with the use of virtual traffic light systems (VTLS) in the intersections. This work implements and evaluates a VTLS conceived to help the pedestrians pass safely the intersections without real traffic lights. The simulated VTLS scenario used two distinct communication paradigms—the pull and push communication models. The pull model was implemented in named data networking (NDN), because NDN uses natively a pull-based communication model, where consumers send requests to pull the contents from the provider. A distinct approach is followed by the push-based model, where consumers subscribe previously the information, and then the producers distribute the available information to those consumers. Comparing the performance of the push and pull models on a VANET with VTLS, it is observed that the push mode presents lower packet loss and generates fewer packets, and consequently occupies less bandwidth, than the pull mode. In fact, for the considered metrics, the VTLS implemented with the pull mode presents no advantage when compared with the push mode.