885 resultados para Information Security Manager
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Chinese Assoc Cryptol Res, State Key Lab Informat Secur, Inst Software, Grad Univ Chinese Acad Sci, Natl Nat Sci Fdn China
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Chinese Assoc Cryptol Res, State Key Lab Informat Secur, Inst Software, Grad Univ Chinese Acad Sci, Natl Nat Sci Fdn China
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Mobile malware has been growing in scale and complexity spurred by the unabated uptake of smartphones worldwide. Android is fast becoming the most popular mobile platform resulting in sharp increase in malware targeting the platform. Additionally, Android malware is evolving rapidly to evade detection by traditional signature-based scanning. Despite current detection measures in place, timely discovery of new malware is still a critical issue. This calls for novel approaches to mitigate the growing threat of zero-day Android malware. Hence, the authors develop and analyse proactive machine-learning approaches based on Bayesian classification aimed at uncovering unknown Android malware via static analysis. The study, which is based on a large malware sample set of majority of the existing families, demonstrates detection capabilities with high accuracy. Empirical results and comparative analysis are presented offering useful insight towards development of effective static-analytic Bayesian classification-based solutions for detecting unknown Android malware.
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In wireless networks, the broadcast nature of the propagation medium makes the communication process vulnerable to malicious nodes (e.g. eavesdroppers) which are in the coverage area of the transmission. Thus, security issues play a vital role in wireless systems. Traditionally, information security has been addressed in the upper layers (e.g. the network layer) through the design of cryptographic protocols. Cryptography-based security aims to design a protocol such that it is computationally prohibitive for the eavesdropper to decode the information. The idea behind this approach relies on the limited computational power of the eavesdroppers. However, with advances in emerging hardware technologies, achieving secure communications relying on protocol-based mechanisms alone become insufficient. Owing to this fact, a new paradigm of secure communications has been shifted to implement the security at the physical layer. The key principle behind this strategy is to exploit the spatial-temporal characteristics of the wireless channel to guarantee secure data transmission without the need of cryptographic protocols.
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The availability of electricity is fundamental to modern society. It is at the top of the list of critical infrastructures and its interruption can have severe consequences. This highly important system is now evolving to become more reliable, efficient, and clean. This evolving infrastructure has become known as the smart grid; and these future smart grid systems will rely heavily on ICT. This infrastructure will require many servers and due to the nature of the grid, many of these systems will be geographically diverse requiring communication links. At the heart of this ICT infrastructure will be security. At each level of the smart grid from smart metering right through to remote sensing and control networks, security will be a key factor for system design consideration. With an increased number of ICT systems in place the security risk also increases. In this paper the authors discuss the changing nature of security in relation to the smart grid by looking at the move from legacy systems to more modern smart grid systems. The potential planes of attack for future smart grid systems are identified, and the general anatomy of a cyber-attack is presented. The authors then introduce the various threat levels of different types of attack and the mitigation techniques that could be put in place for each. Finally, the authors' introduce a Phasor Measurement Unit (PMU) communication system (operated by the authors) that can be used as a test-bed for some of the proposed future security research.
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With over 50 billion downloads and more than 1.3 million apps in Google’s official market, Android has continued to gain popularity amongst smartphone users worldwide. At the same time there has been a rise in malware targeting the platform, with more recent strains employing highly sophisticated detection avoidance techniques. As traditional signature based methods become less potent in detecting unknown malware, alternatives are needed for timely zero-day discovery. Thus this paper proposes an approach that utilizes ensemble learning for Android malware detection. It combines advantages of static analysis with the efficiency and performance of ensemble machine learning to improve Android malware detection accuracy. The machine learning models are built using a large repository of malware samples and benign apps from a leading antivirus vendor. Experimental results and analysis presented shows that the proposed method which uses a large feature space to leverage the power of ensemble learning is capable of 97.3 % to 99% detection accuracy with very low false positive rates.
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Durante as ultimas décadas, os registos de saúde eletrónicos (EHR) têm evoluído para se adaptar a novos requisitos. O cidadão tem-se envolvido cada vez mais na prestação dos cuidados médicos, sendo mais pró ativo e desejando potenciar a utilização do seu registo. A mobilidade do cidadão trouxe mais desafios, a existência de dados dispersos, heterogeneidade de sistemas e formatos e grande dificuldade de partilha e comunicação entre os prestadores de serviços. Para responder a estes requisitos, diversas soluções apareceram, maioritariamente baseadas em acordos entre instituições, regiões e países. Estas abordagens são usualmente assentes em cenários federativos muito complexos e fora do controlo do paciente. Abordagens mais recentes, como os registos pessoais de saúde (PHR), permitem o controlo do paciente, mas levantam duvidas da integridade clinica da informação aos profissionais clínicos. Neste cenário os dados saem de redes e sistemas controlados, aumentando o risco de segurança da informação. Assim sendo, são necessárias novas soluções que permitam uma colaboração confiável entre os diversos atores e sistemas. Esta tese apresenta uma solução que permite a colaboração aberta e segura entre todos os atores envolvidos nos cuidados de saúde. Baseia-se numa arquitetura orientada ao serviço, que lida com a informação clínica usando o conceito de envelope fechado. Foi modelada recorrendo aos princípios de funcionalidade e privilégios mínimos, com o propósito de fornecer proteção dos dados durante a transmissão, processamento e armazenamento. O controlo de acesso _e estabelecido por políticas definidas pelo paciente. Cartões de identificação eletrónicos, ou certificados similares são utilizados para a autenticação, permitindo uma inscrição automática. Todos os componentes requerem autenticação mútua e fazem uso de algoritmos de cifragem para garantir a privacidade dos dados. Apresenta-se também um modelo de ameaça para a arquitetura, por forma a analisar se as ameaças possíveis foram mitigadas ou se são necessários mais refinamentos. A solução proposta resolve o problema da mobilidade do paciente e a dispersão de dados, capacitando o cidadão a gerir e a colaborar na criação e manutenção da sua informação de saúde. A arquitetura permite uma colaboração aberta e segura, possibilitando que o paciente tenha registos mais ricos, atualizados e permitindo o surgimento de novas formas de criar e usar informação clínica ou complementar.
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This paper describes the various Geofencing Components and Existing Models in terms of their Information Security Control Attribute Profiles. The profiles will dictate the security attributes that should accompany each and every Geofencing Model used for Wi-Fi network security control in an organization, thus minimizing the likelihood of malfunctioning security controls. Although it is up to an organization to investigate the best way of implementing information security for itself, by looking at the related models that have been used in the past this paper will present models commonly used to implement information security controls in the organizations. Our findings will highlight the strengths and weaknesses of the various models and present what our experiment and prototype consider as a robust Geofencing Security Model for securing Wi-Fi Networks
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Dissertação de Mestrado apresentada ao Instituto de Contabilidade e Administração do Porto para a obtenção de grau de Mestre em Auditoria, sob a orientação de Luís Silva Rodrigues