Security, trust and cooperation in wireless sensor networks

Wireless sensor networks are a promising technology for many real-world applications such as critical infrastructure monitoring, scientific data gathering, smart buildings, etc.. However, given the typically unattended and potentially unsecured operation environment, there has been an increased number of security threats to sensor networks. In addition, sensor networks have very constrained resources, such as limited energy, memory, computational power, and communication bandwidth. These unique challenges call for new security mechanisms and algorithms. In this dissertation, we propose novel algorithms and models to address some important and challenging security problems in wireless sensor networks. The first part of the dissertation focuses on data trust in sensor networks. Since sensor networks are mainly deployed to monitor events and report data, the quality of received data must be ensured in order to make meaningful inferences from sensor data. We first study a false data injection attack in the distributed state estimation problem and propose a distributed Bayesian detection algorithm, which could maintain correct estimation results when less than one half of the sensors are compromised. To deal with the situation where more than one half of the sensors may be compromised, we introduce a special class of sensor nodes called \textit{trusted cores}. We then design a secure distributed trust aggregation algorithm that can utilize the trusted cores to improve network robustness. We show that as long as there exist some paths that can connect each regular node to one of these trusted cores, the network can not be subverted by attackers. The second part of the dissertation focuses on sensor network monitoring and anomaly detection. A sensor network may suffer from system failures due to loss of links and nodes, or malicious intrusions. Therefore, it is critical to continuously monitor the overall state of the network and locate performance anomalies. The network monitoring and probe selection problem is formulated as a budgeted coverage problem and a Markov decision process. Efficient probing strategies are designed to achieve a flexible tradeoff between inference accuracy and probing overhead. Based on the probing results on traffic measurements, anomaly detection can be conducted. To capture the highly dynamic network traffic, we develop a detection scheme based on multi-scale analysis of the traffic using wavelet transforms and hidden Markov models. The performance of the probing strategy and of the detection scheme are extensively evaluated in malicious scenarios using the NS-2 network simulator. Lastly, to better understand the role of trust in sensor networks, a game theoretic model is formulated to mathematically analyze the relation between trust and cooperation. Given the trust relations, the interactions among nodes are modeled as a network game on a trust-weighted graph. We then propose an efficient heuristic method that explores network heterogeneity to improve Nash equilibrium efficiency

A Mixed-Integer Programming Approach for Jammer Placement Problems for Flow-Jamming Attacks on Wireless Communication Networks

In this dissertation, we study an important problem of security in wireless networks. We study different attacks and defense strategies in general and more specifically jamming attacks. We begin the dissertation by providing a tutorial introducing the operations research community to the various types of attacks and defense strategies in wireless networks. In this tutorial, we give examples of mathematical programming models to model jamming attacks and defense against jamming attacks in wireless networks. Later we provide a comprehensive taxonomic classification of the various types of jamming attacks and defense against jamming attacks. The classification scheme will provide a one stop location for future researchers on various jamming attack and defense strategies studied in literature. This classification scheme also highlights the areas of research in jamming attack and defense against jamming attacks which have received less attention and could be a good area of focus for future research. In the next chapter, we provide a bi-level mathematical programming model to study jamming attack and defense strategy. We solve this using a game-theoretic approach and also study the impact of power level, location of jamming device, and the number of transmission channels available to transmit data on the attack and defense against jamming attacks. We show that by increasing the number of jamming devices the throughput of the network drops by at least 7%. Finally we study a special type of jamming attack, flow-jamming attack. We provide a mathematical programming model to solve the location of jamming devices to increase the impact of flow-jamming attacks on wireless networks. We provide a Benders decomposition algorithm along with some acceleration techniques to solve large problem instances in reasonable amount of time. We draw some insights about the impact of power, location and size of the network on the impact of flow-jamming attacks in wireless networks

Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems

Much research in artificial intelligence is concerned with the development of autonomous agents that can interact effectively with other agents. An important aspect of such agents is the ability to reason about the behaviours of other agents, by constructing models which make predictions about various properties of interest (such as actions, goals, beliefs) of the modelled agents. A variety of modelling approaches now exist which vary widely in their methodology and underlying assumptions, catering to the needs of the different sub-communities within which they were developed and reflecting the different practical uses for which they are intended. The purpose of the present article is to provide a comprehensive survey of the salient modelling methods which can be found in the literature. The article concludes with a discussion of open problems which may form the basis for fruitful future research.Comment: Final manuscript (46 pages), published in Artificial Intelligence Journal. The arXiv version also contains a table of contents after the abstract, but is otherwise identical to the AIJ version. Keywords: autonomous agents, multiagent systems, modelling other agents, opponent modellin

Modelo de confiança para redes AD HOC baseado em teoria de jogos

Orientador: Prof. Dr. Luiz Carlos Pessoa AlbiniCoorientador: Prof. Dr. André L. VignattiDissertação (mestrado) - Universidade Federal do Paraná, Setor de Ciências Exatas, Curso de Pós-Graduação em Informática. Defesa: Curitiba, 31/08/2013Bibliografia: fls. 49-55Resumo: Confiança e tratada como uma explicação para a diferença entre o comportamento humano real e aquele que pode ser explicado pelo desejo individual para maximizar a própria utilidade. Em termos gerais, a confianca e uma atribulo a relacão entre indivíduos ou grupos. Este trabalho propoe um modelo de confianca para Redes Ad Hoc baseado em Teoria de Jogos com o objetivo de responder a seguinte questao: Qual a confiança de um no em outro? O modelo de confiança proposto, chamado TrustUm, calcula o valor de confianca atraves de informacoes trocadas entre os proprios nos e de testes realizados em seus vizinhos. O TrustUm esta dividido em três etapas: monitoramento de vizinhos, troca de informações e calculo de confianca. A troca de informacoes utiliza os conceitos de Teoria de Jogos, utilizando o Jogo do Ultimato, atraves do qual o comportamento dos nos da rede e analisado. Atraves dos resultados obtidos dessa analise e calculado um valor de confiança para cada no da rede. Os resultados demostram que o modelo consegue inicialmente realizar as trocas de mensagens, otimizando o recebimento de informaçcãoes confiáveis. Tambem o resultado aponta um valor de confianca embasado na ancianidade das informacoes trocadas e baseado nas informacoes dos proprios nos. Os resultados apontam uma diminuicão de ate 70% de informacães maliciosas trocadas na rede, alem de um cáalculo de confiancça mais preciso.Abstract: Trust is treated as an explanation for the difference between real and human behavior which can be explained by the desire to maximize their own utility. In general, trust is an assignment to the relationship between individuals or groups. This project proposes a trust model for ad hoc networks based on game theory. The proposal aims to answer the following question: How much a given node trusts another given node? The proposed trust model, called TrustUm calculates the trust value through information exchanged with the nodes themselves and with tests of its neighbors. To this end, some mathematical models were used to guide the calculation, and also by parameters set by the application that will use this model. The TrustUm is divided into three steps: monitoring neighbors, exchange of information and calculation of trust. The exchange of information uses the concepts of Game Theory, using the Ultimatum Game, where the behavior of the network nodes will be analyzed and the results obtained through this analysis will be calculated a trust value to each network node. The results show that the model can first select the message exchanges, optimizing the receipt of reliable information. Furthermore, the result indicates a trust value based on old information and based on information from the nodes. The results show a decrease of 30% to 70% of malicious information exchanged in the network, and a more precise trust value