931 resultados para User interfaces (Computer systems)
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INTRODUCTION In recent years computer systems have become increasingly complex and consequently the challenge of protecting these systems has become increasingly difficult. Various techniques have been implemented to counteract the misuse of computer systems in the form of firewalls, antivirus software and intrusion detection systems. The complexity of networks and dynamic nature of computer systems leaves current methods with significant room for improvement. Computer scientists have recently drawn inspiration from mechanisms found in biological systems and, in the context of computer security, have focused on the human immune system (HIS). The human immune system provides an example of a robust, distributed system that provides a high level of protection from constant attacks. By examining the precise mechanisms of the human immune system, it is hoped the paradigm will improve the performance of real intrusion detection systems. This paper presents an introduction to recent developments in the field of immunology. It discusses the incorporation of a novel immunological paradigm, Danger Theory, and how this concept is inspiring artificial immune systems (AIS). Applications within the context of computer security are outlined drawing direct reference to the underlying principles of Danger Theory and finally, the current state of intrusion detection systems is discussed and improvements suggested.
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Modern software application testing, such as the testing of software driven by graphical user interfaces (GUIs) or leveraging event-driven architectures in general, requires paying careful attention to context. Model-based testing (MBT) approaches first acquire a model of an application, then use the model to construct test cases covering relevant contexts. A major shortcoming of state-of-the-art automated model-based testing is that many test cases proposed by the model are not actually executable. These \textit{infeasible} test cases threaten the integrity of the entire model-based suite, and any coverage of contexts the suite aims to provide. In this research, I develop and evaluate a novel approach for classifying the feasibility of test cases. I identify a set of pertinent features for the classifier, and develop novel methods for extracting these features from the outputs of MBT tools. I use a supervised logistic regression approach to obtain a model of test case feasibility from a randomly selected training suite of test cases. I evaluate this approach with a set of experiments. The outcomes of this investigation are as follows: I confirm that infeasibility is prevalent in MBT, even for test suites designed to cover a relatively small number of unique contexts. I confirm that the frequency of infeasibility varies widely across applications. I develop and train a binary classifier for feasibility with average overall error, false positive, and false negative rates under 5\%. I find that unique event IDs are key features of the feasibility classifier, while model-specific event types are not. I construct three types of features from the event IDs associated with test cases, and evaluate the relative effectiveness of each within the classifier. To support this study, I also develop a number of tools and infrastructure components for scalable execution of automated jobs, which use state-of-the-art container and continuous integration technologies to enable parallel test execution and the persistence of all experimental artifacts.
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Intrusion Detection Systems (IDSs) provide an important layer of security for computer systems and networks, and are becoming more and more necessary as reliance on Internet services increases and systems with sensitive data are more commonly open to Internet access. An IDS’s responsibility is to detect suspicious or unacceptable system and network activity and to alert a systems administrator to this activity. The majority of IDSs use a set of signatures that define what suspicious traffic is, and Snort is one popular and actively developing open-source IDS that uses such a set of signatures known as Snort rules. Our aim is to identify a way in which Snort could be developed further by generalising rules to identify novel attacks. In particular, we attempted to relax and vary the conditions and parameters of current Snort rules, using a similar approach to classic rule learning operators such as generalisation and specialisation. We demonstrate the effectiveness of our approach through experiments with standard datasets and show that we are able to detect previously undetected variants of various attacks. We conclude by discussing the general effectiveness and appropriateness of generalisation in Snort based IDS rule processing. Keywords: anomaly detection, intrusion detection, Snort, Snort rules
Resumo:
INTRODUCTION In recent years computer systems have become increasingly complex and consequently the challenge of protecting these systems has become increasingly difficult. Various techniques have been implemented to counteract the misuse of computer systems in the form of firewalls, antivirus software and intrusion detection systems. The complexity of networks and dynamic nature of computer systems leaves current methods with significant room for improvement. Computer scientists have recently drawn inspiration from mechanisms found in biological systems and, in the context of computer security, have focused on the human immune system (HIS). The human immune system provides an example of a robust, distributed system that provides a high level of protection from constant attacks. By examining the precise mechanisms of the human immune system, it is hoped the paradigm will improve the performance of real intrusion detection systems. This paper presents an introduction to recent developments in the field of immunology. It discusses the incorporation of a novel immunological paradigm, Danger Theory, and how this concept is inspiring artificial immune systems (AIS). Applications within the context of computer security are outlined drawing direct reference to the underlying principles of Danger Theory and finally, the current state of intrusion detection systems is discussed and improvements suggested.
Resumo:
Intrusion Detection Systems (IDSs) provide an important layer of security for computer systems and networks, and are becoming more and more necessary as reliance on Internet services increases and systems with sensitive data are more commonly open to Internet access. An IDS’s responsibility is to detect suspicious or unacceptable system and network activity and to alert a systems administrator to this activity. The majority of IDSs use a set of signatures that define what suspicious traffic is, and Snort is one popular and actively developing open-source IDS that uses such a set of signatures known as Snort rules. Our aim is to identify a way in which Snort could be developed further by generalising rules to identify novel attacks. In particular, we attempted to relax and vary the conditions and parameters of current Snort rules, using a similar approach to classic rule learning operators such as generalisation and specialisation. We demonstrate the effectiveness of our approach through experiments with standard datasets and show that we are able to detect previously undetected variants of various attacks. We conclude by discussing the general effectiveness and appropriateness of generalisation in Snort based IDS rule processing. Keywords: anomaly detection, intrusion detection, Snort, Snort rules
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This document presents GEmSysC, an unified cryptographic API for embedded systems. Software layers implementing this API can be built over existing libraries, allowing embedded software to access cryptographic functions in a consistent way that does not depend on the underlying library. The API complies to good practices for API design and good practices for embedded software development and took its inspiration from other cryptographic libraries and standards. The main inspiration for creating GEmSysC was the CMSIS-RTOS standard, which defines an unified API for embedded software in an implementation-independent way, but targets operating systems instead of cryptographic functions. GEmSysC is made of a generic core and attachable modules, one for each cryptographic algorithm. This document contains the specification of the core of GEmSysC and three of its modules: AES, RSA and SHA-256. GEmSysC was built targeting embedded systems, but this does not restrict its use only in such systems – after all, embedded systems are just very limited computing devices. As a proof of concept, two implementations of GEmSysC were made. One of them was built over wolfSSL, which is an open source library for embedded systems. The other was built over OpenSSL, which is open source and a de facto standard. Unlike wolfSSL, OpenSSL does not specifically target embedded systems. The implementation built over wolfSSL was evaluated in a Cortex- M3 processor with no operating system while the implementation built over OpenSSL was evaluated on a personal computer with Windows 10 operating system. This document displays test results showing GEmSysC to be simpler than other libraries in some aspects. These results have shown that both implementations incur in little overhead in computation time compared to the cryptographic libraries themselves. The overhead of the implementation has been measured for each cryptographic algorithm and is between around 0% and 0.17% for the implementation over wolfSSL and between 0.03% and 1.40% for the one over OpenSSL. This document also presents the memory costs for each implementation.
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A evolução tecnológica tem provocado uma evolução na medicina, através de sistemas computacionais voltados para o armazenamento, captura e disponibilização de informações médicas. Os relatórios médicos são, na maior parte das vezes, guardados num texto livre não estruturado e escritos com vocabulário proprietário, podendo ocasionar falhas de interpretação. Através das linguagens da Web Semântica, é possível utilizar antologias como modo de estruturar e padronizar a informação dos relatórios médicos, adicionando¬ lhe anotações semânticas. A informação contida nos relatórios pode desta forma ser publicada na Web, permitindo às máquinas o processamento automático da informação. No entanto, o processo de criação de antologias é bastante complexo, pois existe o problema de criar uma ontologia que não cubra todo o domínio pretendido. Este trabalho incide na criação de uma ontologia e respectiva povoação, através de técnicas de PLN e Aprendizagem Automática que permitem extrair a informação dos relatórios médicos. Foi desenvolvida uma aplicação, que permite ao utilizador converter relatórios do formato digital para o formato OWL. ABSTRACT: Technological evolution has caused a medicine evolution through computer systems which allow storage, gathering and availability of medical information. Medical reports are, most of the times, stored in a non-structured free text and written in a personal way so that misunderstandings may occur. Through Semantic Web languages, it’s possible to use ontology as a way to structure and standardize medical reports information by adding semantic notes. The information in those reports can, by these means, be displayed on the web, allowing machines automatic information processing. However, the process of creating ontology is very complex, as there is a risk creating of an ontology that not covering the whole desired domain. This work is about creation of an ontology and its population through NLP and Machine Learning techniques to extract information from medical reports. An application was developed which allows the user to convert reports from digital for¬ mat to OWL format.
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These notes follow on from the material that you studied in CSSE1000 Introduction to Computer Systems. There you studied details of logic gates, binary numbers and instruction set architectures using the Atmel AVR microcontroller family as an example. In your present course (METR2800 Team Project I), you need to get on to designing and building an application which will include such a microcontroller. These notes focus on programming an AVR microcontroller in C and provide a number of example programs to illustrate the use of some of the AVR peripheral devices.
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Training-needs analysis is critical for defining and procuring effective training systems. However, traditional approaches to training-needs analysis are not suitable for capturing the demands of highly automated and computerized work domains. In this article, we propose that work domain analysis can identify the functional structure of a work domain that must be captured in a training system, so that workers can be trained to deal with unpredictable contingencies that cannot be handled by computer systems. To illustrate this argument, we outline a work domain analysis of a fighter aircraft that defines its functional structure in terms of its training objectives, measures of performance, basic training functions, physical functionality, and physical context. The functional structure or training needs identified by work domain analysis can then be used as a basis for developing functional specifications for training systems, specifically its design objectives, data collection capabilities, scenario generation capabilities, physical functionality, and physical attributes. Finally, work domain analysis also provides a useful framework for evaluating whether a tendered solution fulfills the training needs of a work domain.
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This paper describes a coupled knowledge-based system (KBS) for the design of liquid-retaining structures, which can handle both the symbolic knowledge processing based on engineering heuristics in the preliminary synthesis stage and the extensive numerical crunching involved in the detailed analysis stage. The prototype system is developed by employing blackboard architecture and a commercial shell VISUAL RULE STUDIO. Its present scope covers design of three types of liquid-retaining structures, namely, a rectangular shape with one compartment, a rectangular shape with two compartments and a circular shape. Through custom-built interactive graphical user interfaces, the user is directed throughout the design process, which includes preliminary design, load specification, model generation, finite element analysis, code compliance checking and member sizing optimization. It is also integrated with various relational databases that provide the system with sectional properties, moment and shear coefficients and final member details. This system can act as a consultant to assist novice designers in the design of liquid-retaining structures with increase in efficiency and optimization of design output and automated record keeping. The design of a typical example of the liquid-retaining structure is also illustrated. (C) 2003 Elsevier B.V All rights reserved.
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When developing interactive applications, considering the correctness of graphical user interfaces (GUIs) code is essential. GUIs are critical components of today's software, and contemporary software tools do not provide enough support for ensuring GUIs' code quality. GUIsurfer, a GUI reverse engineering tool, enables evaluation of behavioral properties of user interfaces. It performs static analysis of GUI code, generating state machines that can help in the evaluation of interactive applications. This paper describes the design, software architecture, and the use of GUIsurfer through an example. The tool is easily re-targetable, and support is available to Java/Swing, and WxHaskell. The paper sets the ground for a generalization effort to consider rich internet applications. It explores the GWT web applications' user interface programming toolkit.
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Graphical user interfaces (GUIs) make software easy to use by providing the user with visual controls. Therefore, correctness of GUI's code is essential to the correct execution of the overall software. Models can help in the evaluation of interactive applications by allowing designers to concentrate on its more important aspects. This paper presents a generic model for language-independent reverse engineering of graphical user interface based applications, and we explore the integration of model-based testing techniques in our approach, thus allowing us to perform fault detection. A prototype tool has been constructed, which is already capable of deriving and testing a user interface behavioral model of applications written in Java/Swing.
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This paper presents a catalog of smells in the context of interactive applications. These so-called usability smells are indicators of poor design on an application’s user interface, with the potential to hinder not only its usability but also its maintenance and evolution. To eliminate such usability smells we discuss a set of program/usability refactorings. In order to validate the presented usability smells catalog, and the associated refactorings, we present a preliminary empirical study with software developers in the context of a real open source hospital management application. Moreover, a tool that computes graphical user interface behavior models, giving the applications’ source code, is used to automatically detect usability smells at the model level.
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The emergence of new business models, namely, the establishment of partnerships between organizations, the chance that companies have of adding existing data on the web, especially in the semantic web, to their information, led to the emphasis on some problems existing in databases, particularly related to data quality. Poor data can result in loss of competitiveness of the organizations holding these data, and may even lead to their disappearance, since many of their decision-making processes are based on these data. For this reason, data cleaning is essential. Current approaches to solve these problems are closely linked to database schemas and specific domains. In order that data cleaning can be used in different repositories, it is necessary for computer systems to understand these data, i.e., an associated semantic is needed. The solution presented in this paper includes the use of ontologies: (i) for the specification of data cleaning operations and, (ii) as a way of solving the semantic heterogeneity problems of data stored in different sources. With data cleaning operations defined at a conceptual level and existing mappings between domain ontologies and an ontology that results from a database, they may be instantiated and proposed to the expert/specialist to be executed over that database, thus enabling their interoperability.
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Visto que o tratamento das águas residuais é um tema muito importante para a saúde pública, é necessário criar vários processos para o tratamento de efluentes. Após a finalização de todos os processos, o efluente tratado terá de cumprir requisitos de qualidade químicos e biológicos para a sua descarga no meio ambiente. A utilização de equipamentos e técnicas, caraterizados por elevados níveis de precisão (como a tecnologia), é muito importante, pois é possível tornar o sistema mais autónomo, monitorizar processos e controlá-los de forma eficiente e acessível para o utilizador. Assim, neste tipo de sistemas terá que ser utilizado um elemento central de controlo e vários elementos auxiliares, nomeadamente vários tipos de sensores. Também terá que se usar uma interface que permita ao utilizador comunicar com o sistema de controlo, de forma a poder manipular e ajustar determinados parâmetros que influenciam os processos de tratamento. Neste sentido, a presente dissertação apresenta um estudo/projeto, na Adega Cooperativa de Mangualde, onde se pretende automatizar, controlar e monitorizar a Estação de Tratamento de Águas Residuais (ETAR) da mesma. Como, cada vez mais, os lucros das empresas dependem do bom funcionamento, não só dos trabalhadores mas também dos seus equipamentos, é necessário que estes estejam em ótimas condições de trabalho, de forma a evitar avarias e paragens na produção, o que vem trazer, por consequência, prejuízos para as empresas. Assim, realizar-se-á, também, um plano de manutenção para garantir o bom desempenho dos equipamentos desta unidade fabril.