The research leading to these results has received funding from the Ministry of Economy and Competitiveness through SEMOLA project (TEC2015-68284-R) and from the Autonomous Region of Madrid through MOSI-AGIL-CM project (grant P2013/ICE-3019, co-funded by EU Structural Funds FSE and FEDER). Borja Bordel has received funding from the Ministry of Education through the FPU program (grant number FPU15/03977). This research has been partially supported by Ministerio de Economía, Industria y Competitividad (MINECO), Agencia Estatal de Investigación (AEI), and Fondo Europeo de Desarrollo Regional (FEDER, UE) under project COPCIS, reference TIN2017-84844-C2-1-R. Future 5G networks must provide communication services to a great and heterogeneous collection of scenarios: from traditional mobile communications, to emerging applications such as Industry 4.0 or the Internet-of-Things (IoT). In this context, the network slicing technique is defined, where network resources are packaged and assigned in an isolated manner to sets of users according to their specific requirements. Two different domains are, thus, defined: the intra-slice domain (where dedicated and specific solutions have to be deployed) and the inter-slice domain (including transversal solutions). One of the key topics which should be redefined following this approach is security. Traditionally, some solutions (such as stream ciphers) were not considered in mobile networks. However, 5G systems will be extensively employed in other new and very distinct scenarios, where requirements are different. For example, the use of resource constrained devices with little mobility and real-time data streaming in certain IoT applications suggests the use of stream ciphers (and other similar techniques) as main security solutions. Therefore, in this paper we investigate and propose a new security solution for emerging 5G networks, to be applied in the intra-slice domain. The proposed solutions employ lightweight pseudo-random number generators in order to provide the keystream used in stream ciphers which protect the private information and hide the communication signals in the frequency spectrum using spread spectrum techniques. We also describe and evaluate a first implementation of the proposed solution, using both, a simulation scenario and a real deployment.

Cyber-Physical Social Sensing (CPSS) is a new trend in the context of pervasive sensing. In these new systems, various domains coexist in time, evolve together and influence each other. Thus, application-specific tools are necessary for specifying and validating designs and simulating systems. However, nowadays, different tools are employed to simulate each domain independently. Mainly, the cause of the lack of co-simulation instruments to simulate all domains together is the extreme difficulty of combining and synchronizing various tools. In order to reduce that difficulty, an adequate architecture for the final co-simulator must be selected. Therefore, in this paper the authors investigate and propose a methodology for the design of CPSS co-simulation tools. The paper describes the four steps that software architects should follow in order to design the most adequate co-simulator for a certain application, considering the final users’ needs and requirements and various additional factors such as the development team’s experience. Moreover, the first practical use case of the proposed methodology is provided. An experimental validation is also included in order to evaluate the performing of the proposed co-simulator and to determine the correctness of the proposal.

Smart Environments (SE) aim to satisfy the experience of individuals by the provision of systems, services and devices. Although many approaches may be followed in order to build a SE, a service-based design is the most promising one nowadays. In the

Smart Homes are one of the most promising real applications of Internet of Things and Cyber-Physical Systems. Devices and software components are deployed to create enhanced living environments where physical information is captured by sensors, sent to servers and finally transmitted to information endpoints to be consumed after its processing. These systems usually employ resource constrained components in dense architectures supported by massive machine type communications. Components, to adapt to different scenarios, present several configuration options. In machine type communications, these configuration options should be selected dynamically and automatically. Many works have addressed this situation in relation to sensor-server communications but endpoints are still mostly manually configured. Therefore, in this paper it is proposed an automatic and dynamic configuration algorithm, based on the idea of “efficiency,” for information endpoints in the context of Smart Homes. Different costs associated to endpoint-server communications in Smart Homes are identified and mathematically modelled. Using this model and real measurements, the most efficient configuration is selected for each endpoint at each moment, not only guarantying the interoperability of devices but also ensuring an adequate resource usage, for example, modifying the endpoints’ lifecycle or the information compression mechanism. In order to validate the proposed solution, an experimental validation including both real implementation and simulation scenarios is provided.