Secure Authentication and Credential Establishment in Narrowband IoT and 5G.

Security is critical in the deployment and maintenance of novel IoT and 5G networks. The process of bootstrapping is required to establish a secure data exchange between IoT devices and data-driven platforms. It entails, among other steps, authentication, authorization, and credential management. Nevertheless, there are few efforts dedicated to providing service access authentication in the area of constrained IoT devices connected to recent wireless networks such as narrowband IoT (NB-IoT) and 5G. Therefore, this paper presents the adaptation of bootstrapping protocols to be compliant with the 3GPP specifications in order to enable the 5G feature of secondary authentication for constrained IoT devices. To allow the secondary authentication and key establishment in NB-IoT and 4G/5G environments, we have adapted two Extensible Authentication Protocol (EAP) lower layers, i.e., PANATIKI and LO-CoAP-EAP. In fact, this approach presents the evaluation of both aforementioned EAP lower layers, showing the contrast between a current EAP lower layer standard, i.e., PANA, and one specifically designed with the constraints of IoT, thus providing high flexibility and scalability in the bootstrapping process in 5G networks. The proposed solution is evaluated to prove its efficiency and feasibility, being one of the first efforts to support secure service authentication and key establishment for constrained IoT devices in 5G environments.

PLUG-N-HARVEST Architecture for Secure and Intelligent Management of Near-Zero Energy Buildings.

Building Automation (BA) is key to encourage the growth of more sustainable cities and smart homes. However, current BA systems are not able to manage new constructions based on Adaptable/Dynamic Building Envelopes (ADBE) achieving near-zero energy-efficiency. The ADBE buildings integrate Renewable Energy Sources (RES) and Envelope Retrofitting (ER) that must be managed by new BA systems based on Artificial Intelligence (AI) and Internet of Things (IoT) through secure protocols. This paper presents the PLUG-N-HARVEST architecture based on cloud AI systems and security-by-design IoT networks to manage near-zero ADBE constructions in both residential and commercial buildings. To demonstrate the PLUG-N-HARVEST architecture, three different real-world pilots have been considered in Germany, Greece and Spain. The paper describes the Spain pilot of residential buildings including the deployment of IoT wireless networks (i.e., sensors and actuators) based on Zwave technology to enable plug-and-play installations. The real-world tests showed the high efficiency of security-by-design Internet communications between building equipment and cloud management systems. Moreover, the results of cloud intelligent management demonstrate the improvements in both energy consumption and comfort conditions.

Enabling Virtual AAA Management in SDN-Based IoT Networks †.

The increase of Software Defined Networks (SDN) and Network Function Virtualization (NFV) technologies is bringing many security management benefits that can be exploited at the edge of Internet of Things (IoT) networks to deal with cyber-threats. In this sense, this paper presents and evaluates a novel policy-based and cyber-situational awareness security framework for continuous and dynamic management of Authentication, Authorization, Accounting (AAA) as well as Channel Protection virtual security functions in IoT networks enabled with SDN/NFV. The virtual AAA, including network authenticators, are deployed as VNF (Virtual Network Function) dynamically at the edge, in order to enable scalable device's bootstrapping and managing the access control of IoT devices to the network. In addition, our solution allows distributing dynamically the necessary crypto-keys for IoT Machine to Machine (M2M) communications and deploy virtual Channel-protection proxys as VNFs, with the aim of establishing secure tunnels among IoT devices and services, according to the contextual decisions inferred by the cognitive framework. The solution has been implemented and evaluated, demonstrating its feasibility to manage dynamically AAA and channel protection in SDN/NFV-enabled IoT scenarios.

A real-time measurement system for long-life flood monitoring and warning applications.

A flood warning system incorporates telemetered rainfall and flow/water level data measured at various locations in the catchment area. Real-time accurate data collection is required for this use, and sensor networks improve the system capabilities. However, existing sensor nodes struggle to satisfy the hydrological requirements in terms of autonomy, sensor hardware compatibility, reliability and long-range communication. We describe the design and development of a real-time measurement system for flood monitoring, and its deployment in a flash-flood prone 650 km(2) semiarid watershed in Southern Spain. A developed low-power and long-range communication device, so-called DatalogV1, provides automatic data gathering and reliable transmission. DatalogV1 incorporates self-monitoring for adapting measurement schedules for consumption management and to capture events of interest. Two tests are used to assess the success of the development. The results show an autonomous and robust monitoring system for long-term collection of water level data in many sparse locations during flood events.