190 resultados para malicious
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Ciência da Computação - IBILCE
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Os Sistemas de Detecção e Prevenção de Intrusão (Intrusion Detection Systems – IDS e Intrusion Prevention Systems - IPS) são ferramentas bastante conhecidas e bem consagradas no mundo da segurança da informação. Porém, a falta de integração com os equipamentos de rede como switches e roteadores acaba limitando a atuação destas ferramentas e exige um bom dimensionamento de recursos de hardware como processamento, memória e interfaces de rede de alta velocidade, utilizados para implementá-las. Diante de diversas limitações deparadas por pesquisadores e administradores de redes, surgiu o conceito de Rede Definida por Software (Software Defined Network – SDN), que ao separar os planos de controle e de dados, permite adaptar o funcionamento da rede de acordo com as necessidades de cada um. Desta forma, devido à padronização e flexibilidade propostas pelas SDNs, e das limitações apresentadas dos IPSs, esta dissertação de mestrado propõe o IPSFlow, um framework que utiliza uma rede baseada na arquitetura SDN e o protocolo OpenFlow para a criação de um IPS com ampla cobertura e que permite bloquear um tráfego caracterizado pelos IDS(s) como malicioso no equipamento mais próximo da origem. Para validar o framework, experimentos no ambiente virtual Mininet foram realizados utilizando-se o Snort como IDS para analisar tráfego de varredura (scan) gerado pelo Nmap de um host ao outro. Os resultados coletados apresentam que o IPSFlow funcionou conforme planejado ao efetuar o bloqueio de 85% do tráfego de varredura.
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Given the exponential growth in the spread of the virus world wide web (Internet) and its increasing complexity, it is necessary to adopt more complex systems for the extraction of malware finger-prints (malware fingerprints - malicious software; is the name given to extracting unique information leading to identification of the virus, equivalent to humans, the fingerprint). The architecture and protocol proposed here aim to achieve more efficient fingerprints, using techniques that make a single fingerprint enough to compromise an entire group of viruses. This efficiency is given by the use of a hybrid approach of extracting fingerprints, taking into account the analysis of the code and the behavior of the sample, so called viruses. The main targets of this proposed system are Polymorphics and Metamorphics Malwares, given the difficulty in creating fingerprints that identify an entire family from these viruses. This difficulty is created by the use of techniques that have as their main objective compromise analysis by experts. The parameters chosen for the behavioral analysis are: File System; Records Windows; RAM Dump and API calls. As for the analysis of the code, the objective is to create, in binary virus, divisions in blocks, where it is possible to extract hashes. This technique considers the instruction there and its neighborhood, characterized as being accurate. In short, with this information is intended to predict and draw a profile of action of the virus and then create a fingerprint based on the degree of kinship between them (threshold), whose goal is to increase the ability to detect viruses that do not make part of the same family
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Ciência da Computação - IBILCE
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Animal cruelty is defined as a deliberate action that causes pain and suffering to an animal. In Brazil, legislation known as the Environmental Crimes Law states that cruelty toward all animal species is criminal in nature. From 644 domestic cats necropsied between January 1998 and December 2009, 191 (29.66%) presented lesions highly suggestive of animal cruelty. The main necroscopic finding was exogenous carbamate poisoning (75.39%) followed by blunt-force trauma (21.99%). Cats from 7 months to 2 years of age were the most affected (50.79%). In Brazil, violence is a public health problem and there is a high prevalence of domestic violence. Therefore, even if laws provide for animal welfare and protection, animals are common targets for violent acts. Within a context of social violence, cruelty toward animals is an important parameter to be considered, and the non-accidental lesions that were found are evidence of malicious actions.
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Gossip protocols have proved to be a viable solution to set-up and manage largescale P2P services or applications in a fully decentralised scenario. The gossip or epidemic communication scheme is heavily based on stochastic behaviors and it is the fundamental idea behind many large-scale P2P protocols. It provides many remarkable features, such as scalability, robustness to failures, emergent load balancing capabilities, fast spreading, and redundancy of information. In some sense, these services or protocols mimic natural system behaviors in order to achieve their goals. The key idea of this work is that the remarkable properties of gossip hold when all the participants follow the rules dictated by the actual protocols. If one or more malicious nodes join the network and start cheating according to some strategy, the result can be catastrophic. In order to study how serious the threat posed by malicious nodes can be and what can be done to prevent attackers from cheating, we focused on a general attack model aimed to defeat a key service in gossip overlay networks (the Peer Sampling Service [JGKvS04]). We also focused on the problem of protecting against forged information exchanged in gossip services. We propose a solution technique for each problem; both techniques are general enough to be applied to distinct service implementations. As gossip protocols, our solutions are based on stochastic behavior and are fully decentralized. In addition, each technique’s behaviour is abstracted by a general primitive function extending the basic gossip scheme; this approach allows the adoptions of our solutions with minimal changes in different scenarios. We provide an extensive experimental evaluation to support the effectiveness of our techniques. Basically, these techniques aim to be building blocks or P2P architecture guidelines in building more resilient and more secure P2P services.
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The noticeable differences in the theoretical and operative definitions of envy across studies and approaches have produced a fragmentary representation and understanding of the envious emotion. The present dissertation aimed to clarify the inherent nature of the construct of envy through the integration of findings from three independent studies. We focused on malicious envy, and investigated it from both a dispositional and an episodic perspective. Studies 1 and 2 investigated the dimensionality of envy as a stable individual characteristic and an episodic emotional state, respectively. In order to elicit episodic envy, a scenario-based experiment was conducted. Results indicated that, in both its dispositional and episodic facets, envy is a bidimensional construct composed by an inner-directed dimension of inferiority and helplessness, and an outer-directed dimension of feelings of anger and ill will. Moreover, findings from Study 1 allowed to establish boundaries between envy and competing constructs that have often been included in conceptualizations of envy. The psychometrically validated definition of envy provided by Studies 1 and 2 represents a valuable contribution to empirical research. Implications for envy research concern the promotion of a shared operationalization of envy in future studies, which will arguably facilitate the comparison of findings between studies and between approaches. Study 3 examined the mechanisms through which dispositional envy affects individuals’ social adjustment and psychological wellbeing. Findings revealed that the detrimental effects of envy on perceived social support and subjective well-being are mostly mediated by other personal characteristics, such as neuroticism and self-esteem. By reducing global self-esteem, the envious disposition may damage supportive social networks via antisocial direct and indirect behaviors that may arise from envy and that are likely to drive others away. On the other hand, by damaging both emotional stability and self-worth, dispositional envy leads to reduced subjective well-being. Implications for clinical practice are discussed.
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One of the most undervalued problems by smartphone users is the security of data on their mobile devices. Today smartphones and tablets are used to send messages and photos and especially to stay connected with social networks, forums and other platforms. These devices contain a lot of private information like passwords, phone numbers, private photos, emails, etc. and an attacker may choose to steal or destroy this information. The main topic of this thesis is the security of the applications present on the most popular stores (App Store for iOS and Play Store for Android) and of their mechanisms for the management of security. The analysis is focused on how the architecture of the two systems protects users from threats and highlights the real presence of malware and spyware in their respective application stores. The work described in subsequent chapters explains the study of the behavior of 50 Android applications and 50 iOS applications performed using network analysis software. Furthermore, this thesis presents some statistics about malware and spyware present on the respective stores and the permissions they require. At the end the reader will be able to understand how to recognize malicious applications and which of the two systems is more suitable for him. This is how this thesis is structured. The first chapter introduces the security mechanisms of the Android and iOS platform architectures and the security mechanisms of their respective application stores. The Second chapter explains the work done, what, why and how we have chosen the tools needed to complete our analysis. The third chapter discusses about the execution of tests, the protocol followed and the approach to assess the “level of danger” of each application that has been checked. The fourth chapter explains the results of the tests and introduces some statistics on the presence of malicious applications on Play Store and App Store. The fifth chapter is devoted to the study of the users, what they think about and how they might avoid malicious applications. The sixth chapter seeks to establish, following our methodology, what application store is safer. In the end, the seventh chapter concludes the thesis.
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With today's prevalence of Internet-connected systems storing sensitive data and the omnipresent threat of technically skilled malicious users, computer security remains a critically important field. Because of today's multitude of vulnerable systems and security threats, it is vital that computer science students be taught techniques for programming secure systems, especially since many of them will work on systems with sensitive data after graduation. Teaching computer science students proper design, implementation, and maintenance of secure systems is a challenging task that calls for the use of novel pedagogical tools. This report describes the implementation of a compiler that converts mandatory access control specification Domain-Type Enforcement Language to the Java Security Manager, primarily for pedagogical purposes. The implementation of the Java Security Manager was explored in depth, and various techniques to work around its inherent limitations were explored and partially implemented, although some of these workarounds do not appear in the current version of the compiler because they would have compromised cross-platform compatibility. The current version of the compiler and implementation details of the Java Security Manager are discussed in depth.
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The ever increasing popularity of apps stems from their ability to provide highly customized services to the user. The flip side is that in order to provide such services, apps need access to very sensitive private information about the user. This leads to malicious apps that collect personal user information in the background and exploit it in various ways. Studies have shown that current app vetting processes which are mainly restricted to install time verification mechanisms are incapable of detecting and preventing such attacks. We argue that the missing fundamental aspect here is a comprehensive and usable mobile privacy solution, one that not only protects the user's location information, but also other equally sensitive user data such as the user's contacts and documents. A solution that is usable by the average user who does not understand or care about the low level technical details. To bridge this gap, we propose privacy metrics that quantify low-level app accesses in terms of privacy impact and transforms them to high-level user understandable ratings. We also provide the design and architecture of our Privacy Panel app that represents the computed ratings in a graphical user-friendly format and allows the user to define policies based on them. Finally, experimental results are given to validate the scalability of the proposed solution.