Secure neighbor discovery in wireless sensor networks using range-free localization techniques

Si una red inalámbrica de sensores se implementa en un entorno hostil, las limitaciones intrínsecas a los nodos conllevan muchos problemas de seguridad. En este artículo se aborda un ataque particular a los protocolos de localización y descubrimiento de vecinos, llevada a cabo por dos nodos que actúan en connivencia y establecen un "agujero de gusano" para tratar de engañar a un nodo aislado, haciéndole creer que se encuentra en la vecindad de un conjunto de nodos locales. Para contrarrestar este tipo de amenazas, se presenta un marco de actuación genéricamente denominado "detection of wormhole attacks using range-free methods" (DWARF) dentro del cual derivamos dos estrategias para de detección de agujeros de gusano: el primer enfoque (DWARFLoc) realiza conjuntamente la localización y la detección de ataques, mientras que el otro (DWARFTest) valida la posición estimada por el nodo una vez finalizado el protocolo de localización. Las simulaciones muestran que ambas estrategias son eficaces en la detección de ataques tipo "agujero de gusano", y sus prestaciones se comparan con las de un test convencional basado en la razón de verosimilitudes.

An Internet of Things approach for managing smart services provided by wearable devices.

The Internet of Things (IoT) is growing at a fast pace with new devices getting connected all the time. A new emerging group of these devices are the wearable devices, and Wireless Sensor Networks are a good way to integrate them in the IoT concept and bring new experiences to the daily life activities. In this paper we present an everyday life application involving a WSN as the base of a novel context-awareness sports scenario where physiological parameters are measured and sent to the WSN by wearable devices. Applications with several hardware components introduce the problem of heterogeneity in the network. In order to integrate different hardware platforms and to introduce a service-oriented semantic middleware solution into a single application, we propose the use of an Enterprise Service Bus (ESB) as a bridge for guaranteeing interoperability and integration of the different environments, thus introducing a semantic added value needed in the world of IoT-based systems. This approach places all the data acquired (e.g., via Internet data access) at application developers disposal, opening the system to new user applications. The user can then access the data through a wide variety of devices (smartphones, tablets, computers) and Operating Systems (Android, iOS, Windows, Linux, etc.).

The Influence of Communication Range on Connectivity for Resilient Wireless Sensor Networks Using a Probabilistic Approach.

Wireless sensor networks (WSNs) consist of thousands of nodes that need to communicate with each other. However, it is possible that some nodes are isolated from other nodes due to limited communication range. This paper focuses on the influence of communication range on the probability that all nodes are connected under two conditions, respectively: (1) all nodes have the same communication range, and (2) communication range of each node is a random variable. In the former case, this work proves that, for 0menor queepsmenor quee^(-1) , if the probability of the network being connected is 0.36eps , by means of increasing communication range by constant C(eps) , the probability of network being connected is at least 1-eps. Explicit function C(eps) is given. It turns out that, once the network is connected, it also makes the WSNs resilient against nodes failure. In the latter case, this paper proposes that the network connection probability is modeled as Cox process. The change of network connection probability with respect to distribution parameters and resilience performance is presented. Finally, a method to decide the distribution parameters of node communication range in order to satisfy a given network connection probability is developed.

SMArc: a proposal for a smart, semantic middleware architecture focused on Smart City energy management

Among the main features that are intended to become part of what can be expected from the Smart City, one of them should be an improved energy management system, in order to benefit from a healthier relation with the environment, minimize energy expenses, and offer dynamic market opportunities. A Smart Grid seems like a very suitable infrastructure for this objective, as it guarantees a two-way information flow that will provide the means for energy management enhancement. However, to obtain all the required information, another entity must care about all the devices required to gather the data. What is more, this entity must consider the lifespan of the devices within the Smart Grid—when they are turned on and off or when new appliances are added—along with the services that devices are able to provide. This paper puts forward SMArc—an acronym for semantic middleware architecture—as a middleware proposal for the Smart Grid, so as to process the collected data and use it to insulate applications from the complexity of the metering facilities and guarantee that any change that may happen at these lower levels will be updated for future actions in the system.

PUE attack detection in CWSN using collaboration and learning behavior

Cognitive Wireless Sensor Network (CWSN) is a new paradigm which integrates cognitive features in traditional Wireless Sensor Networks (WSNs) to mitigate important problems such as spectrum occupancy. Security in Cognitive Wireless Sensor Networks is an important problem because these kinds of networks manage critical applications and data. Moreover, the specific constraints of WSN make the problem even more critical. However, effective solutions have not been implemented yet. Among the specific attacks derived from new cognitive features, the one most studied is the Primary User Emulation (PUE) attack. This paper discusses a new approach, based on anomaly behavior detection and collaboration, to detect the PUE attack in CWSN scenarios. A nonparametric CUSUM algorithm, suitable for low resource networks like CWSN, has been used in this work. The algorithm has been tested using a cognitive simulator that brings important results in this area. For example, the result shows that the number of collaborative nodes is the most important parameter in order to improve the PUE attack detection rates. If the 20% of the nodes collaborates, the PUE detection reaches the 98% with less than 1% of false positives.

Evaluation, energy optimization, and spectrum analysis of an artificial noise technique to improve CWSN security

This paper presents the security evaluation, energy consumption optimization, and spectrum scarcity analysis of artificial noise techniques to increase physical-layer security in Cognitive Wireless Sensor Networks (CWSNs). These techniques introduce noise into the spectrum in order to hide real information. Nevertheless, they directly affect two important parameters in Cognitive Wireless Sensor Networks (CWSNs), energy consumption and spectrum utilization. Both are affected because the number of packets transmitted by the network and the active period of the nodes increase. Security evaluation demonstrates that these techniques are effective against eavesdropper attacks, but also optimization allows for the implementation of these approaches in low-resource networks such as Cognitive Wireless Sensor Networks. In this work, the scenario is formally modeled and the optimization according to the simulation results and the impact analysis over the frequency spectrum are presented.

Cognitive wireless sensor network platform for cooperative communications

Nowadays, Wireless Ad Hoc Sensor Networks (WAHSNs), specially limited in energy and resources, are subject to development constraints and difficulties such as the increasing RF spectrum saturation at the unlicensed bands. Cognitive Wireless Sensor Networks (CWSNs), leaning on a cooperative communication model, develop new strategies to mitigate the inefficient use of the spectrum that WAHSNs face. However, few and poorly featured platforms allow their study due to their early research stage. This paper presents a versatile platform that brings together cognitive properties into WAHSNs. It combines hardware and software modules as an entire instrument to investigate CWSNs. The hardware fits WAHSN requirements in terms of size, cost, features, and energy. It allows communication over three different RF bands, becoming the only cognitive platform for WAHSNs with this capability. In addition, its modular and scalable design is widely adaptable to almost any WAHSN application. Significant features such as radio interface (RI) agility or energy consumption have been proven throughout different performance tests.

A game theory based strategy for reducing energy consumption in cognitive WSN

Wireless sensor networks (WSNs) are one of the most important users of wireless communication technologies in the coming years and some challenges in this area must be addressed for their complete development. Energy consumption and spectrum availability are two of the most severe constraints of WSNs due to their intrinsic nature. The introduction of cognitive capabilities into these networks has arisen to face the issue of spectrum scarcity but could be used to face energy challenges too due to their new range of communication possibilities. In this paper a new strategy based on game theory for cognitive WSNs is discussed. The presented strategy improves energy consumption by taking advantage of the new change-communication-channel capability. Based on game theory, the strategy decides when to change the transmission channel depending on the behavior of the rest of the network nodes. The strategy presented is lightweight but still has higher energy saving rates as compared to noncognitive networks and even to other strategies based on scheduled spectrum sensing. Simulations are presented for several scenarios that demonstrate energy saving rates of around 65% as compared to WSNs without cognitive techniques.

Assessment of species diversity and state of "Stipa tenacissima" steppes

North African steppes are subjected to extreme degradation resulting in the reduction of their surface, genetic erosion of resources, and decrease in biodiversity. "Stipa tenacissima" steppes, which constitute one of the most representative vegetation types in the driest areas of the Mediterranean basin, are continuously degrading. With the aim of contributing to a better knowledge of the floristic composition and diagnosing the state of degradation of these steppes, we conducted a phytoecological analysis of 10 "S. tenacissima" sites in Tunisia. Floristic inventory compiled a systematic list of 46 vascular plant species belonging to 43 genera and 26 families. Species richness ranged from 4 to 18 species per 900 m2. Total vegetation cover was moderate and fluctuated between 22.8% and 49.9%. Our results revealed also a decreasing trend in species richness with increasing elevation (ρ = –0.585). Indeed, species richness was negatively correlated with slope (ρ = –0.19) and positively correlated with sand content (ρ = 0.262). Biological types were dominated by chamaephytes; this chamaephytization is due to the phenomenon of aridization and overgrazing. Moreover, the low species cover and the appearance of nonpalatable species highlighted the vulnerability of these steppes to degradation.