171 research outputs found

    IntelliFlow : um enfoque proativo para adicionar inteligência de ameaças cibernéticas a redes definidas por software

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    Orientador: Christian Rodolfo Esteve RothenbergDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: Segurança tem sido uma das principais preocupações enfrentadas pela computação em rede principalmente, com o aumento das ameaças à medida que a Internet comercial e economias afins crescem rapidamente. Tecnologias de virtualização que permitem serviços em nuvem em escala colocam novos desafios para a segurança das infraestruturas computacionais, exigindo novos mecanismos que combinem o best-of-breed para reagir contra as metodologias de ataque emergentes. Nosso trabalho busca explorar os avanços na Cyber Threat Intelligence (CTI) no contexto da arquitetura de redes definidas por software, ou em inglês, Software Defined Networking (SDN). Enquanto a CTI representa uma abordagem recente para o combate de ameaças baseada em fontes confiáveis, a partir do compartihamento de informação e conhecimento sobre atividades criminais virtuais, a SDN é uma tendência recente na arquitetura de redes computacionais baseada em princípios de modulação e programabilidade. Nesta dissertação, nós propomos IntelliFlow, um sistema de detecção de inteligência para SDN que segue a abordagem proativa usando OpenFlow para efetivar contramedidas para as ameaças aprendidas a partir de um plano de inteligência distribuida. Nós mostramos a partir de uma implementação de prova de conceito que o sistema proposto é capaz de trazer uma série de benefícios em termos de efetividade e eficiência, contribuindo no plano geral para a segurança de projetos de computação de rede modernosAbstract: Security is a major concern in computer networking which faces increasing threats as the commercial Internet and related economies continue to grow. Virtualization technologies enabling scalable Cloud services pose further challenges to the security of computer infrastructures, demanding novel mechanisms combining the best-of-breed to counter certain types of attacks. Our work aims to explore advances in Cyber Threat Intelligence (CTI) in the context of Software Defined Networking (SDN) architectures. While CTI represents a recent approach to combat threats based on reliable sources, by sharing information and knowledge about computer criminal activities, SDN is a recent trend in architecting computer networks based on modularization and programmability principles. In this dissertation, we propose IntelliFlow, an intelligent detection system for SDN that follows a proactive approach using OpenFlow to deploy countermeasures to the threats learned through a distributed intelligent plane. We show through a proof of concept implementation that the proposed system is capable of delivering a number of benefits in terms of effectiveness and efficiency, altogether contributing to the security of modern computer network designsMestradoEngenharia de ComputaçãoMestre em Engenharia Elétrica159905/2013-3CNP

    Security Evaluation of Virtualized Computing Platforms

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    In this thesis, security experiments were conducted to evaluate embedded security protocol performance of two leading server operating systems, Apple’s MAC OS server LION Vs. Microsoft’s Windows server 2012 R2 OS under different types of security attack. Furthermore, experiments were conducted to understand and evaluate the effect of virtualization using Hyper-V with Windows 2012 R2 OS on MAC hardware platform. For these experiments, connection rate, connection latency, non-paged pool allocations and processor core utilization for different OS, virtual machines, and under different traffic types were measured

    Controlled DDoS Attack on IPv4/IPv6 Network Using Distributed Computing Infrastructure

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    The paper focuses on design, background and experimental results of real environment of DDoS attacks. The experimental testbed is based on employment of a tool for IT automation to perform DDoS attacks under monitoring. DDoS attacks are still serious threat in both IPv4 and IPv6 networks and creation of simple tool to test the network for DDoS attack and to allow evaluation of vulnerabilities and DDoS countermeasures of the networks is necessary. In proposed testbed, Ansible orchestration tool is employed to perform and coordinate DDoS attacks. Ansible is a powerful tool and simplifies the implementation of the test environment. Moreover, no special hardware is required for the attacks execution, the testbed uses existing infrastructure in an organization. The case study of implementation of this environment shows straightforwardness to create a testbed comparable with a botnet with ten thousand bots. Furthermore, the experimental results demonstrate the potential of the proposed environment and present the impact of the attacks on particular target servers in IPv4 and IPv6 networks

    Container network functions: bringing NFV to the network edge

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    In order to cope with the increasing network utilization driven by new mobile clients, and to satisfy demand for new network services and performance guarantees, telecommunication service providers are exploiting virtualization over their network by implementing network services in virtual machines, decoupled from legacy hardware accelerated appliances. This effort, known as NFV, reduces OPEX and provides new business opportunities. At the same time, next generation mobile, enterprise, and IoT networks are introducing the concept of computing capabilities being pushed at the network edge, in close proximity of the users. However, the heavy footprint of today's NFV platforms prevents them from operating at the network edge. In this article, we identify the opportunities of virtualization at the network edge and present Glasgow Network Functions (GNF), a container-based NFV platform that runs and orchestrates lightweight container VNFs, saving core network utilization and providing lower latency. Finally, we demonstrate three useful examples of the platform: IoT DDoS remediation, on-demand troubleshooting for telco networks, and supporting roaming of network functions

    Dynamic Shifting of Virtual Network Topologies for Network Attack Prevention

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    Computer networks were not designed with security in mind, making research into the subject of network security vital. Virtual Networks are similar to computer networks, except the components of a Virtual Network are in software rather than hardware. With the constant threat of attacks on networks, security is always a big concern, and Virtual Networks are no different. Virtual Networks have many potential attack vectors similar to physical networks, making research into Virtual Network security of great importance. Virtual Networks, since they are composed of virtualized network components, have the ability to dynamically change topologies. In this paper, we explore Virtual Networks and their ability to quickly shift their network topology. We investigate the potential use of this flexibility to protect network resources and defend against malicious activities. To show the ability of reactively shifting a Virtual Network’s topology to se- cure a network, we create a set of four experiments, each with a different dynamic topology shift, or “dynamic defense”. These four groups of experiments are called the Server Protection, Isolated Subnet, Distributed Port Group, and Standard Port Group experiments. The Server Protection experiments involve detecting an attack against a server and shifting the server behind a protected subnet. The other three sets of experiments, called Attacker Prevention experiments, involve detecting a malicious node in the internal network and initiating a dynamic de- fense to move the attacker behind a protected subnet. Each Attacker Prevention experiment utilizes a different dynamic defense to prevent the malicious node from attacking the rest of the Virtual Network. For each experiment, we run 6 different network attacks to validate the effectiveness of the dynamic defenses. The network attacks utilized for each experiment are ICMP Flooding, TCP Syn Flooding, Smurf attack, ARP Spoofing, DNS Spoofing, and NMAP Scanning. Our validation shows that our dynamic defenses, outside of the standard port group, are very effective in stopping each attack, consistently lowering the at- tacks’ success rate significantly. The Standard Port Group was the one dynamic defense that is ineffective, though there are also a couple of experiments that could benefit from being run with more attackers and with different situations to fully understand the effectiveness of the defenses. We believe that, as Virtual Networks become more common and utilized outside of data centers, the ability to dynamically shift topology can be used for network security purposes

    Detecting Specific Types of DDoS Attacks in Cloud Environment by Using Anomaly Detection

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    RÉSUMÉ Un des avantages les plus importants de l'utilisation du cloud computing est d'avoir des services sur demande, et donc la méthode de paiement dans l'environnement du cloud est de type payer selon l'utilisation (pay per use). Cette caractéristique introduit un nouveau type d'attaque de déni des services appelée déni économique de la durabilité (Economic Denial of Sustainability EDoS) où le client paie des montants supplémentaires au fournisseur du cloud à cause de l'attaque. Les attaques DDoS avec leur nouvelle version sont divisées en trois catégories: 1) Les attaques de consommation de la bande passante. 2) Les attaques qui ciblent des applications spécifiques. 3) Les attaques d'épuisement sur la couche des connections. Dans ce travail, nous avons proposé un nouveau modèle pour détecter précisément les différents types des attaques DDoS et EDoS en comparant le trafic et l'utilisation des ressources dans des situations normale et d'attaque. Des caractéristiques (features) qui sont liées au trafic et à l'utilisation des ressources dans le cas de chaque attaque ont été recueillies. Elles constituent les métriques de notre modèle de détection. Dans la conception de notre modèle, nous avons utilisé les caractéristiques liées à tous les 3 types d'attaques puisque les caractéristiques d'un type d'attaque jouent un rôle important pour détecter un autre type. En effet, pour trouver un point de changement dans l'utilisation des ressources et le comportement du trafic nous avons utilisé l'algorithme des sommes cumulées CUSUM. La précision de notre algorithme a ensuite été étudiée en comparant sa performance avec celle d'un travail populaire précédent. Le taux de détection du modele était élevé, Ce qui indique la haute précision de l'algorithme conçu.----------ABSTRACT One of the most important benefits of using cloud computing is to have on-demand services; accordingly the method of payment in cloud environment is pay per use. This feature results in a new kind of DDOS attack called Economic Denial of Sustainability (EDoS) in which the customer pays extra to the cloud provider because of the attack. DDoS attacks and a new version of these attacks which called EDoS attack are divided into three different categories: 1) Bandwidth–consuming attacks, 2) Attacks which target specific applications and 3) Connection–layer exhaustion attacks. In this work we proposed a novel and inclusive model to precisely detect different types of DDoS and EDoS attacks by comparing the traffic and resource usage in normal and attack situations. Features which are related to traffic and resource usage in each attack were collected as the metrics of our detection model. In designing our model, we used the metrics related to all 3 types of attacks since features of one kind of attack play an important role to detect another type. Moreover, to find a change point in resource usage and traffic behavior we used CUSUM algorithm. The accuracy of our algorithm was then investigated by comparing its performance with one of the popular previous works. Achieving a higher rate of correct detection in our model proved the high accuracy of the designed algorithm

    A Study of Very Short Intermittent DDoS Attacks on the Performance of Web Services in Clouds

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    Distributed Denial-of-Service (DDoS) attacks for web applications such as e-commerce are increasing in size, scale, and frequency. The emerging elastic cloud computing cannot defend against ever-evolving new types of DDoS attacks, since they exploit various newly discovered network or system vulnerabilities even in the cloud platform, bypassing not only the state-of-the-art defense mechanisms but also the elasticity mechanisms of cloud computing. In this dissertation, we focus on a new type of low-volume DDoS attack, Very Short Intermittent DDoS Attacks, which can hurt the performance of web applications deployed in the cloud via transiently saturating the critical bottleneck resource of the target systems by means of external attack HTTP requests outside the cloud or internal resource contention inside the cloud. We have explored external attacks by modeling the n-tier web applications with queuing network theory and implementing the attacking framework based-on feedback control theory. We have explored internal attacks by investigating and exploiting resource contention and performance interference to locate a target VM (virtual machine) and degrade its performance

    Intrusion detection system in software-defined networks

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    Mestrado de dupla diplomação com a UTFPR - Universidade Tecnológica Federal do ParanáSoftware-Defined Networking technologies represent a recent cutting-edge paradigm in network management, offering unprecedented flexibility and scalability. As the adoption of SDN continues to grow, so does the urgency of studying methods to enhance its security. It is the critical importance of understanding and fortifying SDN security, given its pivotal role in the modern digital ecosystem. With the ever-evolving threat landscape, research into innovative security measures is essential to ensure the integrity, confidentiality, and availability of network resources in this dynamic and transformative technology, ultimately safeguarding the reliability and functionality of our interconnected world. This research presents a novel approach to enhancing security in Software-Defined Networking through the development of an initial Intrusion Detection System. The IDS offers a scalable solution, facilitating the transmission and storage of network traffic with robust support for failure recovery across multiple nodes. Additionally, an innovative analysis module incorporates artificial intelligence (AI) to predict the nature of network traffic, effectively distinguishing between malicious and benign data. The system integrates a diverse range of technologies and tools, enabling the processing and analysis of network traffic data from PCAP files, thus contributing to the reinforcement of SDN security.As tecnologias de Redes Definidas por Software representam um paradigma recente na gestão de redes, oferecendo flexibilidade e escalabilidade sem precedentes. À medida que a adoção de soluções SDN continuam a crescer, também aumenta a urgência de estudar métodos para melhorar a sua segurança. É de extrema importância compreender e fortalecer a segurança das SDN, dado o seu papel fundamental no ecossistema digital moderno. Com o cenário de ameaças em constante evolução, a investigação de medidas de segurança inovadoras é essencial para garantir a integridade, a confidencialidade e a disponibilidade dos recursos da rede nesta tecnologia dinâmica e transformadora. Esta investigação apresenta uma nova abordagem para melhorar a segurança nas redes definidas por software através do desenvolvimento de um sistema inicial de deteção de intrusões. O IDS oferece uma solução escalável, facilitando a transmissão e o armazenamento do tráfego de rede com suporte robusto para recuperação de falhas em vários nós. Além disso, um módulo de análise inovador incorpora inteligência artificial (IA) para prever a natureza do tráfego de rede, distinguindo efetivamente entre dados maliciosos e benignos. O sistema integra uma gama diversificada de tecnologias e ferramentas, permitindo o processamento e a análise de dados de tráfego de rede a partir de ficheiros PCAP, contribuindo assim para o reforço da segurança SDN

    Towards Protection Against Low-Rate Distributed Denial of Service Attacks in Platform-as-a-Service Cloud Services

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    Nowadays, the variety of technology to perform daily tasks is abundant and different business and people benefit from this diversity. The more technology evolves, more useful it gets and in contrast, they also become target for malicious users. Cloud Computing is one of the technologies that is being adopted by different companies worldwide throughout the years. Its popularity is essentially due to its characteristics and the way it delivers its services. This Cloud expansion also means that malicious users may try to exploit it, as the research studies presented throughout this work revealed. According to these studies, Denial of Service attack is a type of threat that is always trying to take advantage of Cloud Computing Services. Several companies moved or are moving their services to hosted environments provided by Cloud Service Providers and are using several applications based on those services. The literature on the subject, bring to attention that because of this Cloud adoption expansion, the use of applications increased. Therefore, DoS threats are aiming the Application Layer more and additionally, advanced variations are being used such as Low-Rate Distributed Denial of Service attacks. Some researches are being conducted specifically for the detection and mitigation of this kind of threat and the significant problem found within this DDoS variant, is the difficulty to differentiate malicious traffic from legitimate user traffic. The main goal of this attack is to exploit the communication aspect of the HTTP protocol, sending legitimate traffic with small changes to fill the requests of a server slowly, resulting in almost stopping the access of real users to the server resources during the attack. This kind of attack usually has a small time window duration but in order to be more efficient, it is used within infected computers creating a network of attackers, transforming into a Distributed attack. For this work, the idea to battle Low-Rate Distributed Denial of Service attacks, is to integrate different technologies inside an Hybrid Application where the main goal is to identify and separate malicious traffic from legitimate traffic. First, a study is done to observe the behavior of each type of Low-Rate attack in order to gather specific information related to their characteristics when the attack is executing in real-time. Then, using the Tshark filters, the collection of those packet information is done. The next step is to develop combinations of specific information obtained from the packet filtering and compare them. Finally, each packet is analyzed based on these combinations patterns. A log file is created to store the data gathered after the Entropy calculation in a friendly format. In order to test the efficiency of the application, a Cloud virtual infrastructure was built using OpenNebula Sandbox and Apache Web Server. Two tests were done against the infrastructure, the first test had the objective to verify the effectiveness of the tool proportionally against the Cloud environment created. Based on the results of this test, a second test was proposed to demonstrate how the Hybrid Application works against the attacks performed. The conclusion of the tests presented how the types of Slow-Rate DDoS can be disruptive and also exhibited promising results of the Hybrid Application performance against Low-Rate Distributed Denial of Service attacks. The Hybrid Application was successful in identify each type of Low-Rate DDoS, separate the traffic and generate few false positives in the process. The results are displayed in the form of parameters and graphs.Actualmente, a variedade de tecnologias que realizam tarefas diárias é abundante e diferentes empresas e pessoas se beneficiam desta diversidade. Quanto mais a tecnologia evolui, mais usual se torna, em contraposição, essas empresas acabam por se tornar alvo de actividades maliciosas. Computação na Nuvem é uma das tecnologias que vem sendo adoptada por empresas de diferentes segmentos ao redor do mundo durante anos. Sua popularidade se deve principalmente devido as suas características e a maneira com o qual entrega seus serviços ao cliente. Esta expansão da Computação na Nuvem também implica que usuários maliciosos podem tentar explorá-la, como revela estudos de pesquisas apresentados ao longo deste trabalho. De acordo também com estes estudos, Ataques de Negação de Serviço são um tipo de ameaça que sempre estão a tentar tirar vantagens dos serviços de Computação na Nuvem. Várias empresas moveram ou estão a mover seus serviços para ambientes hospedados fornecidos por provedores de Computação na Nuvem e estão a utilizar várias aplicações baseadas nestes serviços. A literatura existente sobre este tema chama atenção sobre o fato de que, por conta desta expansão na adopção à serviços na Nuvem, o uso de aplicações aumentou. Portanto, ameaças de Negação de Serviço estão visando mais a camada de aplicação e também, variações de ataques mais avançados estão sendo utilizadas como Negação de Serviço Distribuída de Baixa Taxa. Algumas pesquisas estão a ser feitas relacionadas especificamente para a detecção e mitigação deste tipo de ameaça e o maior problema encontrado nesta variante é diferenciar tráfego malicioso de tráfego legítimo. O objectivo principal desta ameaça é explorar a maneira como o protocolo HTTP trabalha, enviando tráfego legítimo com pequenas modificações para preencher as solicitações feitas a um servidor lentamente, tornando quase impossível para usuários legítimos aceder os recursos do servidor durante o ataque. Este tipo de ataque geralmente tem uma janela de tempo curta mas para obter melhor eficiência, o ataque é propagado utilizando computadores infectados, criando uma rede de ataque, transformando-se em um ataque distribuído. Para este trabalho, a ideia para combater Ataques de Negação de Serviço Distribuída de Baixa Taxa é integrar diferentes tecnologias dentro de uma Aplicação Híbrida com o objectivo principal de identificar e separar tráfego malicioso de tráfego legítimo. Primeiro, um estudo é feito para observar o comportamento de cada tipo de Ataque de Baixa Taxa, a fim de recolher informações específicas relacionadas às suas características quando o ataque é executado em tempo-real. Então, usando os filtros do programa Tshark, a obtenção destas informações é feita. O próximo passo é criar combinações das informações específicas obtidas dos pacotes e compará-las. Então finalmente, cada pacote é analisado baseado nos padrões de combinações feitos. Um arquivo de registo é criado ao fim para armazenar os dados recolhidos após o cálculo da Entropia em um formato amigável. A fim de testar a eficiência da Aplicação Híbrida, uma infra-estrutura Cloud virtual foi construída usando OpenNebula Sandbox e servidores Apache. Dois testes foram feitos contra a infra-estrutura, o primeiro teste teve o objectivo de verificar a efectividade da ferramenta proporcionalmente contra o ambiente de Nuvem criado. Baseado nos resultados deste teste, um segundo teste foi proposto para verificar o funcionamento da Aplicação Híbrida contra os ataques realizados. A conclusão dos testes mostrou como os tipos de Ataques de Negação de Serviço Distribuída de Baixa Taxa podem ser disruptivos e também revelou resultados promissores relacionados ao desempenho da Aplicação Híbrida contra esta ameaça. A Aplicação Híbrida obteve sucesso ao identificar cada tipo de Ataque de Negação de Serviço Distribuída de Baixa Taxa, em separar o tráfego e gerou poucos falsos positivos durante o processo. Os resultados são exibidos em forma de parâmetros e grafos
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