The explosive rise of Internet of Things (IoT) systems have notably increased the potential attack surfaces for cybercriminals. Accounting for the features and constraints of IoT devices, traditional security countermeasures can be inefficient in dynamic IoT environments. In this vein, the advantages introduced by Software Defined Networking (SDN) and Network Function Virtualization (NFV) have the potential to reshape the landscape of cybersecurity for IoT systems. To this aim, we provide a comprehensive analysis of security features introduced by NFV and SDN, describing the manifold strategies able to monitor, protect, and react to IoT security threats. We also present lessons learned in the adoption of SDN/NFV-based protection approaches in IoT environments, comparing them with conventional security countermeasures. Finally, we deeply discuss the open challenges related to emerging SDN- and NFV-based security mechanisms, aiming to provide promising directives to conduct future research in this fervent area.

As COVID-19 hounds the world, the common cause of finding a swift solution to manage the pandemic has brought together researchers, institutions, governments, and society at large. The Internet of Things (IoT), artificial intelligence (AI)—including machine learning (ML) and Big Data analytics—as well as Robotics and Blockchain, are the four decisive areas of technological innovation that have been ingenuity harnessed to fight this pandemic and future ones. While these highly interrelated smart and connected health technologies cannot resolve the pandemic overnight and may not be the only answer to the crisis, they can provide greater insight into the disease and support frontline efforts to prevent and control the pandemic. This article provides a blend of discussions on the contribution of these digital technologies, propose several complementary and multidisciplinary techniques to combat COVID-19, offer opportunities for more holistic studies, and accelerate knowledge acquisition and scientific discoveries in pandemic research. First, four areas, where IoT can contribute are discussed, namely: 1) tracking and tracing; 2) remote patient monitoring (RPM) by wearable IoT (WIoT); 3) personal digital twins (PDTs); and 4) real-life use case: ICT/IoT solution in South Korea. Second, the role and novel applications of AI are explained, namely: 1) diagnosis and prognosis; 2) risk prediction; 3) vaccine and drug development; 4) research data set; 5) early warnings and alerts; 6) social control and fake news detection; and 7) communication and chatbot. Third, the main uses of robotics and drone technology are analyzed, including: 1) crowd surveillance; 2) public announcements; 3) screening and diagnosis; and 4) essential supply delivery. Finally, we discuss how distributed ledger technologies (DLTs), of which blockchain is a common example, can be combined with other technologies for tackling COVID-19.

The digital transformation is characterized by the convergence of technologies—from the Internet of Things (IoT) to edge–fog–cloud computing, artificial intelligence (AI), and Blockchain—in multiple dimensions, blurring the lines between the physical and digital worlds. Although these innovations have evolved independently over time, they are increasingly becoming more intertwined, driving the development of new business models. With more adaptation, embracement, and development, we are witnessing a steady convergence and fusion of these technologies resulting in an unprecedented paradigm shift that is expected to disrupt and reshape the next-generation systems in vertical domains in a way that the capabilities of the technologies are aligned in the best possible way to complement each other. Despite the fact that the convergence of the four technologies can potentially tackle the main shortcomings of the existing systems, its adoption is still in its infancy phase, suffering from several issues, such as the absence of consensus toward any reference models or best practices. This article provides a comprehensive insight into the fusions of these paradigms by discussing a blend of topics addressing all the importation aspects from design to deployment. We will begin this article by providing an in-depth discussion on the main requirements, state-of-the-art reference architectures, applications, and challenges. Following this, we will present a reference architecture and a case study on privacy-preserving stress monitoring and management to better elaborate on the corresponding details and considerations.

Since the Internet-of-Things (IoT) has been introduced, it is considered as one of the emerging technologies providing great opportunities to many vertical industries. One of the major IoT application areas that gets significant attention is smart city. Since it is unrealistic to expect full convergence toward a single IoT platform in the near future, it is mandatory to enable interworking between different platforms based on multiple standards, coexisting in the emerging smart cities. In this paper, we take the example of two global IoT standards, FIWARE and oneM2M, which are actively used in many smart city projects, and analyze them to show the feasibility of IoT platforms interworking. Based on the analysis, we design and implement a novel IoT interworking architecture providing a semantic driven integration framework suitable for smart city. The core idea behind our approach is to introduce interworking proxies that: 1) conduct a static mapping of sensor information between IoT platforms and 2) perform semantic interoperability using semantically annotated resources via a semantic interworking proxy that dynamically discovers new kinds of information and adapts itself to enable automatic translation of semantic data between given source and target IoT platforms while it is running. We present the system based on these proxies and evaluate it in Santander smart city. The results demonstrate that it is able to discover and manage IoT sensors connected to both oneM2M and FIWARE. It appears that the semantic approach provides the flexibility and dynamic adaptivity needed for fast growing and rapidly changing urban environments.

With the advancement of Internet-of-Things (IoT) technology, various domains, such as smart factories and smart cars have used this new technology to provide value-added services. In addition, technologies, such as multiaccess edge computing (MEC) and network slicing provide another opportunity for the IoT to support more advanced and real-time services that could not have been previously supported. However, the simple integration of such technologies into the IoT does not take the full advantage of MEC and network slicing or the reduction of latency and traffic prioritization, respectively. Therefore, there is a strong need for an efficient integration mechanism for IoT platforms to maximize the benefit of using such technologies. In this article, we introduce a novel architectural framework that enables the virtualization of an IoT platform with minimum functions to support specific IoT services and host the instance in an edge node, close to the end user. As the instance provides its service at the edge node, where the MEC node and network slice are located, the traffic for the end user does not need to traverse back to the cloud. This architecture guarantees not only low latency but also efficient management of IoT services at the edge node. To show the feasibility of the proposed architecture, we conducted an experimental evaluation by comparing the transmission time of both IoT services running on the central cloud and those using sliced IoT functions in the edge gateway. The results show that the proposed architecture provides twice as much transmission speed as that from the conventional cloud-based IoT platform.

For the last decade the Smart City concept has been under development, fostered by the growing urbanization of the world’s population and the need to handle the challenges that such a scenario raises. During this time many Smart City projects have been executed–some as proof-of-concept, but a growing number resulting in permanent, production-level deployments, improving the operation of the city and the quality of life of its citizens. Thus, Smart Cities are still a highly relevant paradigm which needs further development before it reaches its full potential and provides robust and resilient solutions. In this paper, the focus is set on the Internet of Things (IoT) as an enabling technology for the Smart City. In this sense, the paper reviews the current landscape of IoT-enabled Smart Cities, surveying relevant experiences and city initiatives that have embedded IoT within their city services and how they have generated an impact. The paper discusses the key technologies that have been developed and how they are contributing to the realization of the Smart City. Moreover, it presents some challenges that remain open ahead of us and which are the initiatives and technologies that are under development to tackle them.