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.

The constant and fast increase in the number of heterogeneous Internet of Things (IoT) devices that populate everyday life environments brings new challenges to the full exploitation of the computation, memory, sensing, and actuation resources associated to them. In this context, device virtualization solutions and platforms may definitely play a key role in enabling the desired tradeoff between flexibility and performance. This paper focuses on lightweight virtualization technologies for IoT devices, suitably thought to effectively deploy new integrated applications and to create a novel distributed and virtualized ecosystem. Two different frameworks for container-based IoT service provisioning are compared, the one based on a direct interaction between two cooperating devices and the other based on the presence of a manager supervising the operations between cooperating devices forming a cluster. In the latter case, accounting for the growing impetus to move intelligence toward the edge of the network, management features are implemented at the network access point to provide short latency responses. We also introduce the outcomes of a thorough performance evaluation campaign conducted via a real IoT testbed. The measurements, performed by accounting for the constraints of typical IoT nodes, shed light on the actual feasibility of container-based IoT frameworks.

Mobile Edge Computing (MEC) will play a key role in next‐generation mobile networks to extend the range of supported delay‐sensitive applications. Furthermore, an increasing attention is paid to provide user‐centric services, to better address the strict requirements of novel immersive applications. In this scenario, MEC solutions need to efficiently cope with user mobility, which requires fast relocation of service instances to guarantee the desired Quality of Experience. However, service migration is still an open issue, especially for resource‐constrained edge nodes interconnected by high‐latency and low‐bandwidth links. In this paper, by leveraging the potential of lightweight container‐based virtualization techniques, we investigate a novel approach to support service provisioning in dynamic MEC environments. In particular, we present a framework where proactive service replication for stateless applications is exploited to drastically reduce the time of service migration between different cloudlets and to meet the latency requirements. The performance evaluation shows promising results of our approach with respect to classic reactive service migration.

The Social Internet of Things (SIoT) is a paradigm which is rapidly gaining ground in the Internet of Things (IoT) domain. In the SIoT objects can establish social-like relationships between each others autonomously. In this paper a solution is presented that integrates the SIoT concept in the architecture proposed within the INPUT project. More specifically the feature is exploited of the INPUT project which allows for running the virtual representation of a smart/social object in the access router which is nearest to the physical object. In this way it is expected that delay will decrease and efficiency in the usage of network resources will increase.