2,119 research outputs found

    Security and Privacy Issues in Wireless Mesh Networks: A Survey

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    This book chapter identifies various security threats in wireless mesh network (WMN). Keeping in mind the critical requirement of security and user privacy in WMNs, this chapter provides a comprehensive overview of various possible attacks on different layers of the communication protocol stack for WMNs and their corresponding defense mechanisms. First, it identifies the security vulnerabilities in the physical, link, network, transport, application layers. Furthermore, various possible attacks on the key management protocols, user authentication and access control protocols, and user privacy preservation protocols are presented. After enumerating various possible attacks, the chapter provides a detailed discussion on various existing security mechanisms and protocols to defend against and wherever possible prevent the possible attacks. Comparative analyses are also presented on the security schemes with regards to the cryptographic schemes used, key management strategies deployed, use of any trusted third party, computation and communication overhead involved etc. The chapter then presents a brief discussion on various trust management approaches for WMNs since trust and reputation-based schemes are increasingly becoming popular for enforcing security in wireless networks. A number of open problems in security and privacy issues for WMNs are subsequently discussed before the chapter is finally concluded.Comment: 62 pages, 12 figures, 6 tables. This chapter is an extension of the author's previous submission in arXiv submission: arXiv:1102.1226. There are some text overlaps with the previous submissio

    Smart Wireless Sensor Networks

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    The recent development of communication and sensor technology results in the growth of a new attractive and challenging area - wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors which do not only perceive ambient physical parameters but also be able to process information, cooperate with each other and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption. Special purposes of the applications require design and operation of WSNs different from conventional networks such as the internet. The network design must take into account of the objectives of specific applications. The nature of deployed environment must be considered. The limited of sensor nodes� resources such as memory, computational ability, communication bandwidth and energy source are the challenges in network design. A smart wireless sensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage, reliability and security of network's operation for a maximized lifetime. This book discusses various aspects of designing such smart wireless sensor networks. Main topics includes: design methodologies, network protocols and algorithms, quality of service management, coverage optimization, time synchronization and security techniques for sensor networks

    Compression and encryption for ECG biomedical signal in healthcare system

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    The ECG data needs large memory storage device due to continuous heart rate logs and vital parameter storage. Thus, efficient compression schemes are applied to it before sending it to the telemedicine center for monitoring and analysis. Proper compression mechanisms can not only improve the storage efficiency but also help in faster porting of data from one device to another due to its compact size. Also, the collected ECG signals are processed through various filtering techniques to remove unnecessary noise and then compressed. In our scheme, we propose use of buffer blocks, which is quite novel in this field. Usage of highly efficient methods for peak detection, noise removal, compression and encryption enable seamless and secure transmission of ECG signal from sensor to the monitor. This work further makes use of AES 256 CBC mode, which is barely used in embedded devices, proves to be very strong and efficient in ciphering of the information. The PRD outcome of proposed work comes as 0.41% and CR as 0.35%, which is quite better than existing schemes. Experimental results prove the efficiency of proposed schemes on five distinct signal records from MIT-BIH arrhythmia datasets

    Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

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    Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

    Emerging Communications for Wireless Sensor Networks

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    Wireless sensor networks are deployed in a rapidly increasing number of arenas, with uses ranging from healthcare monitoring to industrial and environmental safety, as well as new ubiquitous computing devices that are becoming ever more pervasive in our interconnected society. This book presents a range of exciting developments in software communication technologies including some novel applications, such as in high altitude systems, ground heat exchangers and body sensor networks. Authors from leading institutions on four continents present their latest findings in the spirit of exchanging information and stimulating discussion in the WSN community worldwide

    Community computation

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 171-186).In this thesis we lay the foundations for a distributed, community-based computing environment to tap the resources of a community to better perform some tasks, either computationally hard or economically prohibitive, or physically inconvenient, that one individual is unable to accomplish efficiently. We introduce community coding, where information systems meet social networks, to tackle some of the challenges in this new paradigm of community computation. We design algorithms, protocols and build system prototypes to demonstrate the power of community computation to better deal with reliability, scalability and security issues, which are the main challenges in many emerging community-computing environments, in several application scenarios such as community storage, community sensing and community security. For example, we develop a community storage system that is based upon a distributed P2P (peer-to-peer) storage paradigm, where we take an array of small, periodically accessible, individual computers/peer nodes and create a secure, reliable and large distributed storage system. The goal is for each one of them to act as if they have immediate access to a pool of information that is larger than they could hold themselves, and into which they can contribute new stuff in a both open and secure manner. Such a contributory and self-scaling community storage system is particularly useful where reliable infrastructure is not readily available in that such a system facilitates easy ad-hoc construction and easy portability. In another application scenario, we develop a novel framework of community sensing with a group of image sensors. The goal is to present a set of novel tools in which software, rather than humans, examines the collection of images sensed by a group of image sensors to determine what is happening in the field of view. We also present several design principles in the aspects of community security. In one application example, we present community-based email spain detection approach to deal with email spams more efficiently.by Fulu Li.Ph.D

    Energy aware optimization for low power radio technologies

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    The explosive growth of IoT is pushing the market towards cheap, very low power devices with a strong focus on miniaturization, for applications such as in-body sensors, personal health monitoring and microrobots. Proposing procedures for energy efficiency in IoT is a difficult task, as it is a rapidly growing market comprised of many and very diverse product categories using technologies that are not stable, evolving at a high pace. The research in this field proposes solutions that go from physical layer optimization up to the network layer, and the sensor network designer has to select the techniques that are best for its application specific architecture and radio technology used. This work is focused on exploring new techniques for enhancing the energy efficiency and user experience of IoT networks. We divide the proposed techniques in frame and chip level optimization techniques, respectively. While the frame level techniques are meant to improve the performance of existing radio technologies, the chip level techniques aim at replacing them with crystal-free architectures. The identified frame level techniques are the use of preamble authentication and packet fragmentation, advisable for Low Power Wide Area Networks (LPWANs), a technology that offers the lowest energy consumption per provided service, but is vulnerable in front of energy exhaustion attacks and does not perform well in dense networks. The use of authenticated preambles between the sensors and gateways becomes a defence mechanism against the battery draining intended by attackers. We show experimentally that this approach is able to reduce with 91% the effect of an exhaustion attack, increasing the device's lifetime from less than 0.24 years to 2.6 years. The experiments were conducted using Loadsensing sensor nodes, commercially used for critical infrastructure control and monitoring. Even if exemplified on LoRaWAN, the use of preamble authentication is extensible to any wireless protocol. The use of packet fragmentation despite the packet fits the frame, is shown to reduce the probability of collisions while the number of users in the duty-cycle restricted network increases. Using custom-made Matlab simulations, important goodput improvement was obtained with fragmentation, with higher impact in slower and denser networks. Using NS3 simulations, we showed that combining packet fragmentation with group NACK can increase the network reliability, while reducing the energy consumed for retransmissions, at the cost of adding small headers to each fragment. It is a strategy that proves to be effective in dense duty-cycle restricted networks only, where the headers overhead is negligible compared to the network traffic. As a chip level technique, we consider using radios for communication that do not use external frequency references such as crystal oscillators. This would enable having all sensor's elements on a single piece of silicon, rendering it even ten times more energy efficient due to the compactness of the chip. The immediate consequence is the loss of communication accuracy and ability to easily switch communication channels. In this sense, we propose a sequence of frequency synchronization algorithms and phases that have to be respected by a crystal-free device so that it can be able to join a network by finding the beacon channel, synthesize all communication channels and then maintain their accuracy against temperature change. The proposed algorithms need no additional network overhead, as they are using the existing network signaling. The evaluation is made in simulations and experimentally on a prototype implementation of an IEEE802.15.4 crystal-free radio. While in simulations we are able to change to another communication channel with very good frequency accuracy, the results obtained experimentally show an initial accuracy slightly above 40ppm, which will be later corrected by the chip to be below 40 ppm.El crecimiento significativo de la IoT está empujando al mercado hacia el desarrollo de dispositivos de bajo coste, de muy bajo consumo energético y con un fuerte enfoque en la miniaturización, para aplicaciones que requieran sensores corporales, monitoreo de salud personal y micro-robots. La investigación en el campo de la eficiencia energética en la IoT propone soluciones que van desde la optimización de la capa física hasta la capa de red. Este trabajo se centra en explorar nuevas técnicas para mejorar la eficiencia energética y la experiencia del usuario de las redes IoT. Dividimos las técnicas propuestas en técnicas de optimización de nivel de trama de red y chip, respectivamente. Si bien las técnicas de nivel de trama están destinadas a mejorar el rendimiento de las tecnologías de radio existentes, las técnicas de nivel de chip tienen como objetivo reemplazarlas por arquitecturas que no requieren de cristales. Las técnicas de nivel de trama desarrolladas en este trabajo son el uso de autenticación de preámbulos y fragmentación de paquetes, aconsejables para redes LPWAN, una tecnología que ofrece un menor consumo de energía por servicio prestado, pero es vulnerable frente a los ataques de agotamiento de energía y no escalan frente la densificación. El uso de preámbulos autenticados entre los sensores y las pasarelas de enlace se convierte en un mecanismo de defensa contra el agotamiento del batería previsto por los atacantes. Demostramos experimentalmente que este enfoque puede reducir con un 91% el efecto de un ataque de agotamiento, aumentando la vida útil del dispositivo de menos de 0.24 años a 2.6 años. Los experimentos se llevaron a cabo utilizando nodos sensores de detección de carga, utilizados comercialmente para el control y monitoreo de infrastructura crítica. Aunque la técnica se ejemplifica en el estándar LoRaWAN, el uso de autenticación de preámbulo es extensible a cualquier protocolo inalámbrico. En esta tesis se muestra también que el uso de la fragmentación de paquetes a pesar de que el paquete se ajuste a la trama, reduce la probabilidad de colisiones mientras aumenta el número de usuarios en una red con restricciones de ciclos de transmisión. Mediante el uso de simulaciones en Matlab, se obtiene una mejora importante en el rendimiento de la red con la fragmentación, con un mayor impacto en redes más lentas y densas. Usando simulaciones NS3, demostramos que combinar la fragmentación de paquetes con el NACK en grupo se puede aumentar la confiabilidad de la red, al tiempo que se reduce la energía consumida para las retransmisiones, a costa de agregar pequeños encabezados a cada fragmento. Como técnica de nivel de chip, consideramos el uso de radios para la comunicación que no usan referencias de frecuencia externas como los osciladores basados en un cristal. Esto permitiría tener todos los elementos del sensor en una sola pieza de silicio, lo que lo hace incluso diez veces más eficiente energéticamente debido a la integración del chip. La consecuencia inmediata, en el uso de osciladores digitales en vez de cristales, es la pérdida de precisión de la comunicación y la capacidad de cambiar fácilmente los canales de comunicación. En este sentido, proponemos una secuencia de algoritmos y fases de sincronización de frecuencia que deben ser respetados por un dispositivo sin cristales para que pueda unirse a una red al encontrar el canal de baliza, sintetizar todos los canales de comunicación y luego mantener su precisión contra el cambio de temperatura. Los algoritmos propuestos no necesitan una sobrecarga de red adicional, ya que están utilizando la señalización de red existente. La evaluación se realiza en simulaciones y experimentalmente en una implementación prototipo de una radio sin cristal IEEE802.15.4. Los resultados obtenidos experimentalmente muestran una precisión inicial ligeramente superior a 40 ppm, que luego será corregida por el chip para que sea inferior a 40 ppm.Postprint (published version

    Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

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    Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig
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