A Hybrid Algorithm for Reliable and Energy-efficient Data Gathering in Wireless Sensor Networks

Reliability and energy efficiency are two important requirements of the data gathering process in wireless sensor networks. Accordingly, we propose a novel data gathering algorithm which meets these requirements. The proposed scheme categorizes the sensed data into valuable and normal data and handles each type of data based on its demands. The main requirement of valuable data is reliability. Thus, the adopted strategy to gather this type of data is to send several copies of data packets toward the sink. The rise of energy exhaustion in this scheme is tolerable. This is due to that, the valuable data is generated at a low rate. On the other hand, our main concern in gathering normal data is energy efficiency. As most of the sensed data is normal, an energy-efficient approach to gather normal data results in considerable energy conserving. Thus, we exploit clustering technique for normal data gathering. We also propose a lightweight intrusion detection system to detect malicious nodes. Simulation results and theoretical analysis confirm that our proposed algorithm provides reliability and energy efficiency at an acceptable level

A cooperative watchdog model based on Dempster–Shafer for detecting misbehaving vehicles

In this paper, we address the problem of detecting misbehaving vehicles in Vehicular Ad Hoc Network (VANET) using Quality of Service Optimized Link State Routing (QoS-OLSR) protocol. According to this protocol, vehicles might misbehave either during the clusters’ formation by claiming bogus information or after clusters are formed. A vehicle is considered as selfish or misbehaving once it over-speeds the maximum speed limit or under-speeds the minimum speed limit where such a behavior will lead to a disconnected network. As a solution, we propose a two-phase model that is able to motivate nodes to behave cooperatively during clusters’ formation and detect misbehaving nodes after clusters are formed. Incentives are given in the form of reputation and linked to network’s services to motivate vehicles to behave cooperatively during the first phase. Misbehaving vehicles can still benefit from network’s services by behaving normally during the clusters’ formation and misbehave after clusters are formed. To detect misbehaving vehicles, cooperative watchdog model based on Dempster–Shafer is modeled where evidences are aggregated and cooperative decision is made. Simulation results show that the proposed detection model is able to increase the probability of detection, decrease the false negatives, and reduce the percentage of selfish nodes in the vehicular network, while maintaining the Quality of Service and stability.PublishedN/

From MANET to people-centric networking: Milestones and open research challenges

In this paper, we discuss the state of the art of (mobile) multi-hop ad hoc networking with the aim to present the current status of the research activities and identify the consolidated research areas, with limited research opportunities, and the hot and emerging research areas for which further research is required. We start by briefly discussing the MANET paradigm, and why the research on MANET protocols is now a cold research topic. Then we analyze the active research areas. Specifically, after discussing the wireless-network technologies, we analyze four successful ad hoc networking paradigms, mesh networks, opportunistic networks, vehicular networks, and sensor networks that emerged from the MANET world. We also present an emerging research direction in the multi-hop ad hoc networking field: people centric networking, triggered by the increasing penetration of the smartphones in everyday life, which is generating a people-centric revolution in computing and communications

Um sistema de detecção de ataques Sinkhole sobre 6lowpan para internet das coisas

Orientador : Prof. Aldri Luiz dos SantosCo-orientadora : Profª. Michele Nogueira LimaDissertação (mestrado) - Universidade Federal do Paraná, Setor de Ciências Exatas, Programa de Pós-Graduação em Informática. Defesa: Curitiba, 18/08/2014Inclui referênciasResumo: A Internet das coisas (IoT) é fruto de uma revolução tecnológica que representa o futuro da computação e da comunicação, sendo identificada como uma das tecnologias emergentes que mudará nossa forma de vida. As redes IoT são formadas por objetos heterogêneos (nós) com alguma inteligência, isto é, com capacidade de processamento que lhes permitem, entre outras tarefas, enviar e receber informações através da rede. Entretanto, cada vez mais objetos estarão interligados com aparelhos digitais, veículos e demais, e a presença deles tende a crescer em nossas vidas trazendo mais comodidade e facilidade. A IoT ligará todos esses objetos, assim como ligará outros que não pertencem à computação podendo ser fixos ou móveis. Visto que os objetos que compõem a IoT possuem recursos limitados, estes se tornarão vulneráveis a vários tipos de ataques, sendo o ataque sinkhole um dos mais destrutivos nas redes. Contudo, as soluções existentes para a proteção e segurança contra os ataques sinkhole geram um elevado consumo de recursos e usam mecanismos complexos para garantir um bom desempenho. Desta forma, este trabalho propõe um sistema de detecção de intrusão, chamado de INTI (Detecção Intrução contra ataques SiNkhole sobre 6LoWPAN para a InterneT das CoIsas) para identificar a presença de ataques sinkhole no serviço de roteamento na IoT. Além disso, INTI visa mitigar os efeitos adversos encontrados em IDSs que perturbam o seu desempenho como falsos positivos e negativos, também como os elevados consumos de recursos. O INTI combina o uso dos mecanismos como o uso de watchdog, reputação e confiança. O mecanismo de watchdog possibilita o monitoramento das atividades dos outros nós durante o encaminhamento de pacotes. A reputação e a confiança colaboram para determinar os dispositivos considerados confiáveis e não confiáveis na rede IoT. Estes mecanismos são utilizados para a detecção de ataques sinkhole, analisando o comportamento dos dispositivos. O sistema INTI foi avaliado em dois cenários realísticos de IoT, e nesses cenários os resultados obtidos mostram a eficácia do INTI em termos de taxa de detecção de ataques, o número de falsos negativos e falsos positivos e da eficiência na taxa de entrega, na latência e no consumo de energia. Palavras-chave: IDS, IoT, segurança, proteção, ataques sinkhole, watchdog, reputação.Abstract: The Internet of Things (IoT) is the result of a technological revolution that represents the future of computing and communication, being identified as one of the emerging technologies that will change our way of life. The IoT networks are formed by heterogeneous objects (nodes) with some intelligence, that is, with processing capabilities that enable them, among other tasks, send and receive information across the network. However, more and more objects are interconnected with digital devices, vehicles and other equipment, and their presence tends to grow in our lives bringing more convenience and ease. The IoT will connect all of these devices as well as bind other objects that do not belong to the digital world and that can be fixed or mobile. Since the objects that make up the IoT have limited resources, they become vulnerable to various attacks, and the sinkhole attack is one of the most destructive in the networks. However, existing solutions for the protection and security against sinkhole attacks generate a high consumption of resources and use complex mechanisms to ensure good performance. Thus, this dissertation proposes an intrusion detection system, called INTI (intrusion detection against sinkhole attacks on 6LoWPAN for IoT), to identify the presence of sinkhole attacks on the routing services in IoT. Moreover, INTI aims to mitigate adverse effects found in IDS that disturb its performance, suck as false positive and negative as well as the high resource cost. The INTI system combines the use of mechanisms such as watchdog, reputation and trust. The watchdog mechanism enables the monitoring the activities of other nodes for packet forwarding. The reputation and trust mechanisms collaborate to determine the devices considered reliable and unreliable in IoT network.These mechanisms are used for detection of attackers, by analyzing the behavior of devices. The INTI system was evaluated in two realistic scenarios of IoT, and these scenarios the results show the effectiveness of INTI in terms of attack detection rate, the number of false negatives and false positives and efficiency in the delivery rate, latency and energy consumption. Keywords: IDS, IoT, security, safety, sinkhole attacks, watchdog, reputation

Game-Theoretic Foundations for Forming Trusted Coalitions of Multi-Cloud Services in the Presence of Active and Passive Attacks

The prominence of cloud computing as a common paradigm for offering Web-based services has led to an unprecedented proliferation in the number of services that are deployed in cloud data centers. In parallel, services' communities and cloud federations have gained an increasing interest in the recent past years due to their ability to facilitate the discovery, composition, and resource scaling issues in large-scale services' markets. The problem is that the existing community and federation formation solutions deal with services as traditional software systems and overlook the fact that these services are often being offered as part of the cloud computing technology, which poses additional challenges at the architectural, business, and security levels. The motivation of this thesis stems from four main observations/research gaps that we have drawn through our literature reviews and/or experiments, which are: (1) leading cloud services such as Google and Amazon do not have incentives to group themselves into communities/federations using the existing community/federation formation solutions; (2) it is quite difficult to find a central entity that can manage the community/federation formation process in a multi-cloud environment; (3) if we allow services to rationally select their communities/federations without considering their trust relationships, these services might have incentives to structure themselves into communities/federations consisting of a large number of malicious services; and (4) the existing intrusion detection solutions in the domain of cloud computing are still ineffective in capturing advanced multi-type distributed attacks initiated by communities/federations of attackers since they overlook the attacker's strategies in their design and ignore the cloud system's resource constraints. This thesis aims to address these gaps by (1) proposing a business-oriented community formation model that accounts for the business potential of the services in the formation process to motivate the participation of services of all business capabilities, (2) introducing an inter-cloud trust framework that allows services deployed in one or disparate cloud centers to build credible trust relationships toward each other, while overcoming the collusion attacks that occur to mislead trust results even in extreme cases wherein attackers form the majority, (3) designing a trust-based game theoretical model that enables services to distributively form trustworthy multi-cloud communities wherein the number of malicious services is minimal, (4) proposing an intra-cloud trust framework that allows the cloud system to build credible trust relationships toward the guest Virtual Machines (VMs) running cloud-based services using objective and subjective trust sources, (5) designing and solving a trust-based maxmin game theoretical model that allows the cloud system to optimally distribute the detection load among VMs within a limited budget of resources, while considering Distributed Denial of Service (DDoS) attacks as a practical scenario, and (6) putting forward a resource-aware comprehensive detection and prevention system that is able to capture and prevent advanced simultaneous multi-type attacks within a limited amount of resources. We conclude the thesis by uncovering some persisting research gaps that need further study and investigation in the future