The expected advent of the Internet of Things (IoT) has triggered a large demand of embedded devices, which envisions the autonomous interaction of sensors and actuators while offering all sort of smart services. However, these IoT devices are limited in computation, storage, and network capacity, which makes them easy to hack and compromise. To achieve secure development of IoT, it is necessary to engineer scalable security solutions optimized for the IoT ecosystem. To this end, Software Defined Networking (SDN) is a promising paradigm that serves as a pillar in the fifth generation of mobile systems (5G) that could help to detect and mitigate Denial of Service (DoS) and Distributed DoS (DDoS) threats. In this work, we propose to experimentally evaluate an entropy-based solution to detect and mitigate DoS and DDoS attacks in IoT scenarios using a stateful SDN data plane. The obtained results demonstrate for the first time the effectiveness of this technique targeting real IoT data traffic.

Mobile communications are growing and the number of users is constantly increasing at an accelerated rate, as well as the demand for the services they request. In the last few years, many efforts have focused on the design and deployment of the new fifth generation (5G) cellular networks. However, novel highly demanding applications, which are already emerging, need to go beyond 5G in order to meet the requirements in terms of network performance. But, at the same time, as the Earth does not allow us to increase the carbon footprint anymore, the energy consumption of the communication networks has to be critically taken into consideration. A multi-objective approach for addressing all these issues is therefore required. This work develops a cellular network framework that allows the evaluation of different system parameters over dynamic traffic patterns, as well as optimizing the different conflicting objectives simultaneously. The novelty relies on that the optimization process integrates key performance indicators from different layers of the network, namely the radio and the network layers, aiming at reaching solutions that account for the power consumption of the base stations, the total capacity provided to mobile users and also the signaling cost generated by handovers. Moreover, new metrics are needed to evaluate different solutions. Starting from the well-known energy efficiency merit factor (bits/Joule), three new merit factors are proposed to classify the network performance since they take into account several network parameters at the same time. These indicators show us the ideal working point that can be used to plan the point of operation of the network. These operation points are a medium-high power and capacity load and a low signaling load.

Currently different reference models are used to manage cybersecurity, although practically none are applicable “as is” to lower levels as they do not detail specific procedural aspects for them. However, they urge organizations to develop a methodological foundation to manage cybersecurity at those levels. Although they allow organizations to adhere to a recognized standard at the strategic level, this advantage vanishes when organizations must define specific low-level procedures, allowing the appearance of inconsistency at tactical and operational levels between departments of the same organization or between organizations. The design of these elements with the required holism and homogeneity is difficult, and this is why generic processes focused on getting certified regarding a standard are usually originated, but they are insufficient to obtain effective cybersecurity because they are not focused on dealing with real cyber threats. Because of the great responsibility of lower levels to achieve effective cybersecurity, this lack of methodological definition makes it difficult to adapt cybersecurity to the highly dynamic cyber context with the required holism and strategic alignment. Our proposal provides CyberTOMP, a process for managing cybersecurity at lower levels, as well as a set of methodological elements that support it. The novelty of these contributions is that they complement the strategic standard selected by the organization, providing it with a set of procedural elements ready to be used out of the box, contributing those aspects required by high-level frameworks to manage cybersecurity at lower levels, for which there is no alternative with a managerial approach.

Mobile Internet data traffic has experienced an exponential growth over the last few years due to the rise of demanding multimedia content and the increasing number of mobile devices. Seamless mobility support at the IP level is envisioned as a key architectural requirement in order to deal with the ever-increasing demand for data and to efficiently utilize a plethora of different wireless access networks. Current efforts from both industry and academia aim to evolve the mobility management protocols towards a more distributed operation to tackle shortcomings of fully centralized approaches. However, distributed solutions face several challenges that can result in lower performance which might affect real-time and multimedia applications. In this paper, we conduct an analytical and simulated evaluation of the main centralized and proposed Distributed Mobility Management (DMM) solutions. Our results show that, in some scenarios, when users move at high speed and/or when the mobile node is running long-lasting applications, the DMM approaches incur high signaling cost and long handover latency.

Mobile Internet data traffic has experienced an exponential growth over the last few years due to the rise of demanding multimedia content applications and the increasing number of smart mobile devices. Seamless mobility support at the network level is envisioned as a key architectural requirement to deal with the ever increasing demand for data and content, cell densification and to efficiently utilize a plethora of heterogeneous wireless access networks (HetNets). Current and emerging efforts on that frontier aim to evolve mobility management protocols towards a more distributed operation to tackle shortcomings that stem from fully centralized oriented approaches. However, as will be detailed hereafter, there are instances where distributed mobility management result in lower performance, which might affect real time and several over the top (OTT) applications (as well as incur increased levels of signaling overhead in the network). To this end, in this paper we provide a meticulous analysis of the different trade-offs between centralized and Distributed Mobility Management (DMM) and based on the analysis we propose a Hybrid DMM solution that overcomes, in terms of mobility costs, both centralized and distributed mobility management protocols. Furthermore, we also conduct a comprehensive analytic and numerical comparison of the different mobility solutions. Our results indicate the significant benefits in terms of packet delivery cost and signaling overhead that Hybrid DMM solutions might bring. Finally, we conclude by discussing some open ended issues in mobility management in emerging and future wireless networks.