Security in Mobile Networks: Communication and Localization

Nowadays the mobile networks are everywhere. The world is becoming more dependent on wireless and mobile services, but the rapid growth of these technologies usually underestimates security aspects. As wireless and mobile services grow, weaknesses in network infrastructures become clearer. One of the problems is privacy. Wireless technologies can reduce costs, increase efficiencies, and make important information more readily and widely available. But, there are also risks. Without appropriate safeguards, these data can be read and modified by unauthorized users. There are many solutions, less and more effective, to protect the data from unauthorized users. But, a specific application could distinguish more data flows between authorized users. Protect the privacy of these information between subsets of users is not a trivial problem. Another problem is the reliability of the wireless service. Multi-vehicle systems composed of Autonomous Guided Vehicles (AGVs) are largely used for industrial transportation in manufacturing and logistics systems. These vehicles use a mobile wireless network to exchange information in order to coordinate their tasks and movements. The reliable dissemination of these information is a crucial operation, because the AGVs may achieve an inconsistent view of the system leading to the failure of the coordination task. This has clear safety implications. Going more in deep, even if the communication are confidential and reliable, anyway the positioning information could be corrupted. Usually, vehicles get the positioning information through a secondary wireless network system such as GPS. Nevertheless, the widespread civil GPS is extremely fragile in adversarial scenarios. An insecure distance or position estimation could produce security problems such as unauthorized accesses, denial of service, thefts, integrity disruption with possible safety implications and intentional disasters. In this dissertation, we face these three problems, proposing an original solution for each one

Collaborative, Intelligent, and Adaptive Systems for the Low-Power Internet of Things

With the emergence of the Internet of Things (IoT), more and more devices are getting equipped with communication capabilities, often via wireless radios. Their deployments pave the way for new and mission-critical applications: cars will communicate with nearby vehicles to coordinate at intersections; industrial wireless closed-loop systems will improve operational safety in factories; while swarms of drones will coordinate to plan collision-free trajectories. To achieve these goals, IoT devices will need to communicate, coordinate, and collaborate over the wireless medium. However, these envisioned applications necessitate new characteristics that current solutions and protocols cannot fulfill: IoT devices require consistency guarantees from their communication and demand for adaptive behavior in complex and dynamic environments.In this thesis, we design, implement, and evaluate systems and mechanisms to enable safe coordination and adaptivity for the smallest IoT devices. To ensure consistent coordination, we bring fault-tolerant consensus to low-power wireless communication and introduce Wireless Paxos, a flavor of the Paxos algorithm specifically tailored to low-power IoT. We then present STARC, a wireless coordination mechanism for intersection management combining commit semantics with synchronous transmissions. To enable adaptivity in the wireless networking stack, we introduce Dimmer and eAFH. Dimmer combines Reinforcement Learning and Multi-Armed Bandits to adapt its communication parameters and counteract the adverse effects of wireless interference at runtime while optimizing energy consumption in normal conditions. eAFH provides dynamic channel management in Bluetooth Low Energy by excluding and dynamically re-including channels in scenarios with mobility. Finally, we demonstrate with BlueSeer that a device can classify its environment, i.e., recognize whether it is located in a home, office, street, or transport, solely from received Bluetooth Low Energy signals fed into an embedded machine learning model. BlueSeer therefore increases the intelligence of the smallest IoT devices, allowing them to adapt their behaviors to their current surroundings

Coordination and Self-Adaptive Communication Primitives for Low-Power Wireless Networks

The Internet of Things (IoT) is a recent trend where objects are augmented with computing and communication capabilities, often via low-power wireless radios. The Internet of Things is an enabler for a connected and more sustainable modern society: smart grids are deployed to improve energy production and consumption, wireless monitoring systems allow smart factories to detect faults early and reduce waste, while connected vehicles coordinate on the road to ensure our safety and save fuel. Many recent IoT applications have stringent requirements for their wireless communication substrate: devices must cooperate and coordinate, must perform efficiently under varying and sometimes extreme environments, while strict deadlines must be met. Current distributed coordination algorithms have high overheads and are unfit to meet the requirements of today\u27s wireless applications, while current wireless protocols are often best-effort and lack the guarantees provided by well-studied coordination solutions. Further, many communication primitives available today lack the ability to adapt to dynamic environments, and are often tuned during their design phase to reach a target performance, rather than be continuously updated at runtime to adapt to reality.In this thesis, we study the problem of efficient and low-latency consensus in the context of low-power wireless networks, where communication is unreliable and nodes can fail, and we investigate the design of a self-adaptive wireless stack, where the communication substrate is able to adapt to changes to its environment. We propose three new communication primitives: Wireless Paxos brings fault-tolerant consensus to low-power wireless networking, STARC is a middleware for safe vehicular coordination at intersections, while Dimmer builds on reinforcement learning to provide adaptivity to low-power wireless networks. We evaluate in-depth each primitive on testbed deployments and we provide an open-source implementation to enable their use and improvement by the community

Green Cellular Networks: A Survey, Some Research Issues and Challenges

Energy efficiency in cellular networks is a growing concern for cellular operators to not only maintain profitability, but also to reduce the overall environment effects. This emerging trend of achieving energy efficiency in cellular networks is motivating the standardization authorities and network operators to continuously explore future technologies in order to bring improvements in the entire network infrastructure. In this article, we present a brief survey of methods to improve the power efficiency of cellular networks, explore some research issues and challenges and suggest some techniques to enable an energy efficient or "green" cellular network. Since base stations consume a maximum portion of the total energy used in a cellular system, we will first provide a comprehensive survey on techniques to obtain energy savings in base stations. Next, we discuss how heterogeneous network deployment based on micro, pico and femto-cells can be used to achieve this goal. Since cognitive radio and cooperative relaying are undisputed future technologies in this regard, we propose a research vision to make these technologies more energy efficient. Lastly, we explore some broader perspectives in realizing a "green" cellular network technologyComment: 16 pages, 5 figures, 2 table

Byzantine fault-tolerant agreement protocols for wireless Ad hoc networks

Tese de doutoramento, Informática (Ciências da Computação), Universidade de Lisboa, Faculdade de Ciências, 2010.The thesis investigates the problem of fault- and intrusion-tolerant consensus in resource-constrained wireless ad hoc networks. This is a fundamental problem in distributed computing because it abstracts the need to coordinate activities among various nodes. It has been shown to be a building block for several other important distributed computing problems like state-machine replication and atomic broadcast. The thesis begins by making a thorough performance assessment of existing intrusion-tolerant consensus protocols, which shows that the performance bottlenecks of current solutions are in part related to their system modeling assumptions. Based on these results, the communication failure model is identified as a model that simultaneously captures the reality of wireless ad hoc networks and allows the design of efficient protocols. Unfortunately, the model is subject to an impossibility result stating that there is no deterministic algorithm that allows n nodes to reach agreement if more than n2 omission transmission failures can occur in a communication step. This result is valid even under strict timing assumptions (i.e., a synchronous system). The thesis applies randomization techniques in increasingly weaker variants of this model, until an efficient intrusion-tolerant consensus protocol is achieved. The first variant simplifies the problem by restricting the number of nodes that may be at the source of a transmission failure at each communication step. An algorithm is designed that tolerates f dynamic nodes at the source of faulty transmissions in a system with a total of n 3f + 1 nodes. The second variant imposes no restrictions on the pattern of transmission failures. The proposed algorithm effectively circumvents the Santoro- Widmayer impossibility result for the first time. It allows k out of n nodes to decide despite dn 2 e(nk)+k2 omission failures per communication step. This algorithm also has the interesting property of guaranteeing safety during arbitrary periods of unrestricted message loss. The final variant shares the same properties of the previous one, but relaxes the model in the sense that the system is asynchronous and that a static subset of nodes may be malicious. The obtained algorithm, called Turquois, admits f < n 3 malicious nodes, and ensures progress in communication steps where dnf 2 e(n k f) + k 2. The algorithm is subject to a comparative performance evaluation against other intrusiontolerant protocols. The results show that, as the system scales, Turquois outperforms the other protocols by more than an order of magnitude.Esta tese investiga o problema do consenso tolerante a faltas acidentais e maliciosas em redes ad hoc sem fios. Trata-se de um problema fundamental que captura a essência da coordenação em actividades envolvendo vários nós de um sistema, sendo um bloco construtor de outros importantes problemas dos sistemas distribuídos como a replicação de máquina de estados ou a difusão atómica. A tese começa por efectuar uma avaliação de desempenho a protocolos tolerantes a intrusões já existentes na literatura. Os resultados mostram que as limitações de desempenho das soluções existentes estão em parte relacionadas com o seu modelo de sistema. Baseado nestes resultados, é identificado o modelo de falhas de comunicação como um modelo que simultaneamente permite capturar o ambiente das redes ad hoc sem fios e projectar protocolos eficientes. Todavia, o modelo é restrito por um resultado de impossibilidade que afirma não existir algoritmo algum que permita a n nós chegaram a acordo num sistema que admita mais do que n2 transmissões omissas num dado passo de comunicação. Este resultado é válido mesmo sob fortes hipóteses temporais (i.e., em sistemas síncronos) A tese aplica técnicas de aleatoriedade em variantes progressivamente mais fracas do modelo até ser alcançado um protocolo eficiente e tolerante a intrusões. A primeira variante do modelo, de forma a simplificar o problema, restringe o número de nós que estão na origem de transmissões faltosas. É apresentado um algoritmo que tolera f nós dinâmicos na origem de transmissões faltosas em sistemas com um total de n 3f + 1 nós. A segunda variante do modelo não impõe quaisquer restrições no padrão de transmissões faltosas. É apresentado um algoritmo que contorna efectivamente o resultado de impossibilidade Santoro-Widmayer pela primeira vez e que permite a k de n nós efectuarem progresso nos passos de comunicação em que o número de transmissões omissas seja dn 2 e(n k) + k 2. O algoritmo possui ainda a interessante propriedade de tolerar períodos arbitrários em que o número de transmissões omissas seja superior a . A última variante do modelo partilha das mesmas características da variante anterior, mas com pressupostos mais fracos sobre o sistema. Em particular, assume-se que o sistema é assíncrono e que um subconjunto estático dos nós pode ser malicioso. O algoritmo apresentado, denominado Turquois, admite f < n 3 nós maliciosos e assegura progresso nos passos de comunicação em que dnf 2 e(n k f) + k 2. O algoritmo é sujeito a uma análise de desempenho comparativa com outros protocolos na literatura. Os resultados demonstram que, à medida que o número de nós no sistema aumenta, o desempenho do protocolo Turquois ultrapassa os restantes em mais do que uma ordem de magnitude.FC

Channel Access Management in Data Intensive Sensor Networks

There are considerable challenges for channel access in Data Intensive Sensor Networks - DISN, supporting Data Intensive Applications like Structural Health Monitoring. As the data load increases, considerable degradation of the key performance parameters of such sensor networks is observed. Successful packet delivery ratio drops due to frequent collisions and retransmissions. The data glut results in increased latency and energy consumption overall. With the considerable limitations on sensor node resources like battery power, this implies that excessive transmissions in response to sensor queries can lead to premature network death. After a certain load threshold the performance characteristics of traditional WSNs become unacceptable. Research work indicates that successful packet delivery ratio in 802.15.4 networks can drop from 95% to 55% as the offered network load increases from 1 packet/sec to 10 packets/sec. This result in conjunction with the fact that it is common for sensors in an SHM system to generate 6-8 packets/sec of vibration data makes it important to design appropriate channel access schemes for such data intensive applications.In this work, we address the problem of significant performance degradation in a special-purpose DISN. Our specific focus is on the medium access control layer since it gives a fine-grained control on managing channel access and reducing energy waste. The goal of this dissertation is to design and evaluate a suite of channel access schemes that ensure graceful performance degradation in special-purpose DISNs as the network traffic load increases.First, we present a case study that investigates two distinct MAC proposals based on random access and scheduling access. The results of the case study provide the motivation to develop hybrid access schemes. Next, we introduce novel hybrid channel access protocols for DISNs ranging from a simple randomized transmission scheme that is robust under channel and topology dynamics to one that utilizes limited topological information about neighboring sensors to minimize collisions and energy waste. The protocols combine randomized transmission with heuristic scheduling to alleviate network performance degradation due to excessive collisions and retransmissions. We then propose a grid-based access scheduling protocol for a mobile DISN that is scalable and decentralized. The grid-based protocol efficiently handles sensor mobility with acceptable data loss and limited overhead. Finally, we extend the randomized transmission protocol from the hybrid approaches to develop an adaptable probability-based data transmission method. This work combines probabilistic transmission with heuristics, i.e., Latin Squares and a grid network, to tune transmission probabilities of sensors, thus meeting specific performance objectives in DISNs. We perform analytical evaluations and run simulation-based examinations to test all of the proposed protocols

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

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