Acquisition and Analysis of Digital Evidencein Android Smartphones

From an expert's standpoint, an Android phone is a large data repositorythat can be stored either locally or remotely. Besides, its platform allows analysts toacquire device data and evidence, collecting information about its owner and facts underinvestigation. This way, by means of exploring and cross referencing that rich data source,one can get information related to unlawful acts and its perpetrator. There are widespreadand well documented approaches to forensic examining mobile devices and computers.Nevertheless, they are neither specific nor detailed enough to be conducted on Androidcell phones. These approaches are not totally adequate to examine modern smartphones,since these devices have internal memories whose removal or mirroring procedures areconsidered invasive and complex, due to difficulties in having direct hardware access. Theexam and analysis are not supported by forensic tools when having to deal with specific filesystems, such as YAFFS2 (Yet Another Flash File System). Furthermore, specific featuresof each smartphone platform have to be considered prior to acquiring and analyzing itsdata. In order to deal with those challenges, this paper proposes a method to perform dataacquisition and analysis of Android smartphones, regardless of version and manufacturer.The proposed approach takes into account existing techniques of computer and cellphone forensic examination, adapting them to specific Android characteristics, its datastorage structure, popular applications and the conditions under which the device wassent to the forensic examiner. The method was defined in a broad manner, not namingspecific tools or techniques. Then, it was deployed into the examination of six Androidsmartphones, which addressed different scenarios that an analyst might face, and wasvalidated to perform an entire evidence acquisition and analysis

Módulos multimídia para o ensino de sistemas de telecomunicações

A tecnologia multimídia fornece elementos para uma concepção integridade transmissão do conhecimento, onde se exige maior comprometimento por parte do aluno, aumentando a sua responsabilidade, encorajando-o ao controle do seu aprendizado. A capacidade de combinar aplicações práticas, visualizações de fenômenos complexos, laboratórios virtuais, animações e a utilização auto assistida de aplicativos de simulação são algumas das vantagens da educação baseada em técnicas multimídia. Este trabalho descreve o desenvolvimento de um ambiente multimídia na forma de CD-ROM, para a área de Sistemas de Telecomunicações. OCD-ROM foi concebido para ser utilizado em atividades de extensão, de maneira a facilitar a aprendizagem e atualização do estudante, de forma mais descentralizada, considerando seus interesses e sua disponibilidade

Atlas de acesso à justiça : indicadores nacionais de acesso à justiça

Supervisão: Flávio Crocce Caetano

A Model for the Definition, Prioritization and Optimization of Indicators

Context: The definition and prioritization of indicators is now a common reality and an integral part of the evolution of the strategic, technical and business processes of any organization, whether public or private. Purpose: This paper proposes a new model regarding the definition and prioritization of indicators. Herein, we also investigate the definition and prioritization models currently adopted by academia and industry, and analyze the context of the proposed strategies against the traditional view of indicator definition currently adopted. In addition, we conducted a survey with organizations that had well-defined indicator management processes, seeking to identify customer expectations with a new indicator management model proposed by this work. Method: To gather evidence, we defined a methodology that relates the literature review and an exploratory case study with the application of an experiment. Driven by a set of research questions, this methodology comprised four main phases: planning, literature review, experiment execution and documentation of results. The method used is supported by some techniques, such as design thinking, design sprint and the Cynefin framework. Results: The analysis of the results was carried out in two different ways: Through the verification of the achievement of specific objectives and through a questionnaire applied to assess the degrees of perception of all employees who participated in the work. Regarding the specific objectives, it is clear that most of the objectives were achieved. Regarding the applied questionnaire, it is clear that, although the collaborators did not have adequate knowledge regarding the conceptual and practical aspects of some approaches used in the proposed model, there was a general perception that the model, in fact, supported top management for decision making. For professionals, the proposed model has a restricted scope; that is, it does not serve all types of organizations. Conclusion: The model proposed in this work proved to be effective, considering that the indicators were defined, prioritized and optimized, with a focus on the user experience. As future work, we intend to expand the scope of the model’s performance, evaluating business indicators alongside IT indicators

Atlas de acesso à justiça : indicadores nacionais de acesso à justiça

Supervisão: Flávio Crocce Caetano

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Mecanismo de otimização para sobrevivência em WLAN : estudo de caso de rede IEEE 802.11.

Tese (doutorado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2006.Este trabalho apresenta um mecanismo para melhorar a sobrevivência de redes locais sem fio (WLAN) padrão IEEE 802.11. A abordagem adotada consiste em duas fases principais: Projeto e Resposta à falha. Na fase de Projeto, a quantificação, posicionamento e configuração dos pontos de acesso (AP) são abordados de acordo com critérios de cobertura da área e de desempenho. Além disso, um esquema de balanceamento de carga é aplicado para melhorar a qualidade de serviço entregue dentro do ambiente planejado. O modelo do projeto de WLAN é baseado em uma técnica heurística de solução para resolver o problema do projeto de rede formulado como um problema de satisfação de restrições. Avalia-se a definição de restrições adicionais ao problema formulado a fim de introduzir propriedades de sobrevivência ao projeto de rede. Na fase da Resposta à falha é considerada a re-configuração dos APs ativos a fim de lidar com a falha de AP(s) na área de serviço. Mudanças no nível de potência e na realocação dos canais de freqüência dos APs em funcionamento são analisadas, procurando a melhor configuração durante a condição de falha. Também é feita uma proposta de métricas de área de cobertura e de desempenho para avaliar a eficiência da solução na condição de falha, de acordo com as restrições de sobrevivência definidas na fase de Projeto. Finalmente, uma implementação de baixo custo das técnicas propostas usando Simple Network Management Protocol (SNMP) é apresentada. _______________________________________________________________________________ ABSTRACTThis work presents a mechanism to improve survivability in IEEE 802.11 WLAN. The approach used consists of two main phases: Design and Fault Response. In the Design phase, quantifying, placement and setting up of APs according to both area coverage and performance criteria is dealt with. Moreover, a load balance scheme is applied to improve the quality of service delivered within the planned environment. The WLAN design model is based on a heuristic solution technique to solve the network design problem formulated as a Constraint Satisfaction Problem (CSP). The definition of additional constraints to the problem formulated in order to introduce survivability properties to the network design is evaluated. In Fault Response phase, the reconfiguration of active APs is considered in order to deal with AP (s) fault in the service area. Changes in both power level (extension of coverage area) and frequency channel assignment (interference avoidance) of the remaining APs are analyzed, searching for the best configuration during the fault condition. A proposal is also made regarding coverage area and performance metrics to evaluate the effectiveness of the solution for the fault condition, according to the fault tolerance constrains defined in the Design phase. Finally, a cost-effective implementation of the proposed techniques using Simple Network Management Protocol (SNMP) is presented