859 resultados para SQL SERVER


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SQL Injection Attack (SQLIA) remains a technique used by a computer network intruder to pilfer an organisation’s confidential data. This is done by an intruder re-crafting web form’s input and query strings used in web requests with malicious intent to compromise the security of an organisation’s confidential data stored at the back-end database. The database is the most valuable data source, and thus, intruders are unrelenting in constantly evolving new techniques to bypass the signature’s solutions currently provided in Web Application Firewalls (WAF) to mitigate SQLIA. There is therefore a need for an automated scalable methodology in the pre-processing of SQLIA features fit for a supervised learning model. However, obtaining a ready-made scalable dataset that is feature engineered with numerical attributes dataset items to train Artificial Neural Network (ANN) and Machine Leaning (ML) models is a known issue in applying artificial intelligence to effectively address ever evolving novel SQLIA signatures. This proposed approach applies numerical attributes encoding ontology to encode features (both legitimate web requests and SQLIA) to numerical data items as to extract scalable dataset for input to a supervised learning model in moving towards a ML SQLIA detection and prevention model. In numerical attributes encoding of features, the proposed model explores a hybrid of static and dynamic pattern matching by implementing a Non-Deterministic Finite Automaton (NFA). This combined with proxy and SQL parser Application Programming Interface (API) to intercept and parse web requests in transition to the back-end database. In developing a solution to address SQLIA, this model allows processed web requests at the proxy deemed to contain injected query string to be excluded from reaching the target back-end database. This paper is intended for evaluating the performance metrics of a dataset obtained by numerical encoding of features ontology in Microsoft Azure Machine Learning (MAML) studio using Two-Class Support Vector Machines (TCSVM) binary classifier. This methodology then forms the subject of the empirical evaluation.

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SQL injection is a common attack method used to leverage infor-mation out of a database or to compromise a company’s network. This paper investigates four injection attacks that can be conducted against the PL/SQL engine of Oracle databases, comparing two recent releases (10g, 11g) of Oracle. The results of the experiments showed that both releases of Oracle were vulner-able to injection but that the injection technique often differed in the packages that it could be conducted in.

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Recent years have seen an astronomical rise in SQL Injection Attacks (SQLIAs) used to compromise the confidentiality, authentication and integrity of organisations’ databases. Intruders becoming smarter in obfuscating web requests to evade detection combined with increasing volumes of web traffic from the Internet of Things (IoT), cloud-hosted and on-premise business applications have made it evident that the existing approaches of mostly static signature lack the ability to cope with novel signatures. A SQLIA detection and prevention solution can be achieved through exploring an alternative bio-inspired supervised learning approach that uses input of labelled dataset of numerical attributes in classifying true positives and negatives. We present in this paper a Numerical Encoding to Tame SQLIA (NETSQLIA) that implements a proof of concept for scalable numerical encoding of features to a dataset attributes with labelled class obtained from deep web traffic analysis. In the numerical attributes encoding: the model leverages proxy in the interception and decryption of web traffic. The intercepted web requests are then assembled for front-end SQL parsing and pattern matching by applying traditional Non-Deterministic Finite Automaton (NFA). This paper is intended for a technique of numerical attributes extraction of any size primed as an input dataset to an Artificial Neural Network (ANN) and statistical Machine Learning (ML) algorithms implemented using Two-Class Averaged Perceptron (TCAP) and Two-Class Logistic Regression (TCLR) respectively. This methodology then forms the subject of the empirical evaluation of the suitability of this model in the accurate classification of both legitimate web requests and SQLIA payloads.

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To store, update and retrieve data from database management systems (DBMS), software architects use tools, like call-level interfaces (CLI), which provide standard functionalities to interact with DBMS. However, the emerging of NoSQL paradigm, and particularly new NoSQL DBMS providers, lead to situations where some of the standard functionalities provided by CLI are not supported, very often due to their distance from the relational model or due to design constraints. As such, when a system architect needs to evolve, namely from a relational DBMS to a NoSQL DBMS, he must overcome the difficulties conveyed by the features not provided by NoSQL DBMS. Choosing the wrong NoSQL DBMS risks major issues with components requesting non-supported features. This paper focuses on how to deploy features that are not so commonly supported by NoSQL DBMS (like Stored Procedures, Transactions, Save Points and interactions with local memory structures) by implementing them in standard CLI.

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The popularity of cloud computing has led to a dramatic increase in the number of data centers in the world. The ever-increasing computational demands along with the slowdown in technology scaling has ushered an era of power-limited servers. Techniques such as near-threshold computing (NTC) can be used to improve energy efficiency in the post-Dennard scaling era. This paper describes an architecture based on the FD-SOI process technology for near-threshold operation in servers. Our work explores the trade-offs in energy and performance when running a wide range of applications found in private and public clouds, ranging from traditional scale-out applications, such as web search or media streaming, to virtualized banking applications. Our study demonstrates the benefits of near-threshold operation and proposes several directions to synergistically increase the energy proportionality of a near-threshold server.

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O CERN - a Organização Europeia para a Investigação Nuclear - é um dos maiores centros de investigação a nível mundial, responsável por diversas descobertas na área da física bem como na área das ciências da computação. O CERN Document Server, também conhecido como CDS Invenio, é um software desenvolvido no CERN, que tem como objectivo fornecer um conjunto de ferramentas para gerir bibliotecas digitais. A fim de melhorar as funcionalidades do CDS Invenio foi criado um novo módulo, chamado BibCirculation, para gerir os livros (e outros itens) da biblioteca do CERN, funcionando como um sistema integrado de gestão de bibliotecas. Esta tese descreve os passos que foram dados para atingir os vários objectivos deste projecto, explicando, entre outros, o processo de integração com os outros módulos existentes bem como a forma encontrada para associar informações dos livros com os metadados do CDS lnvenio. É também possível encontrar uma apresentação detalhada sobre todo o processo de implementação e os testes realizados. Finalmente, são apresentadas as conclusões deste projecto e o trabalho a desenvolver futuramente. ABSTRACT: CERN - The European Organization for Nuclear Research - is one of the largest research centers worldwide, responsible for several discoveries in physics as well as in computer science. The CERN Document Server, also known as CDS Invenio, is a software developed at CERN, which aims to provide a set of tools for managing digital libraries. ln order to improve the functionalities of CDS Invenio a new module was developed, called BibCirculation, to manage books (and other items) from the CERN library, and working as an Integrated Library System. This thesis shows the steps that have been done to achieve the several goals of this project, explaining, among others aspects, the process of integration with other existing modules as well as the way to associate the information about books with the metadata from CDS lnvenio. You can also find detailed explanation of the entire implementation process and testing. Finally, there are presented the conclusions of this project and ideas for future development.

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Universidade Estadual de Campinas. Faculdade de Educação Física

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Technical evaluation of analytical data is of extreme relevance considering it can be used for comparisons with environmental quality standards and decision-making as related to the management of disposal of dredged sediments and the evaluation of salt and brackish water quality in accordance with CONAMA 357/05 Resolution. It is, therefore, essential that the project manager discusses the environmental agency's technical requirements with the laboratory contracted for the follow-up of the analysis underway and even with a view to possible re-analysis when anomalous data are identified. The main technical requirements are: (1) method quantitation limits (QLs) should fall below environmental standards; (2) analyses should be carried out in laboratories whose analytical scope is accredited by the National Institute of Metrology (INMETRO) or qualified or accepted by a licensing agency; (3) chain of custody should be provided in order to ensure sample traceability; (4) control charts should be provided to prove method performance; (5) certified reference material analysis or, if that is not available, matrix spike analysis, should be undertaken and (6) chromatograms should be included in the analytical report. Within this context and with a view to helping environmental managers in analytical report evaluation, this work has as objectives the discussion of the limitations of the application of SW 846 US EPA methods to marine samples, the consequences of having data based on method detection limits (MDL) and not sample quantitation limits (SQL), and present possible modifications of the principal method applied by laboratories in order to comply with environmental quality standards.

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Background: The post-genomic era has brought new challenges regarding the understanding of the organization and function of the human genome. Many of these challenges are centered on the meaning of differential gene regulation under distinct biological conditions and can be performed by analyzing the Multiple Differential Expression (MDE) of genes associated with normal and abnormal biological processes. Currently MDE analyses are limited to usual methods of differential expression initially designed for paired analysis. Results: We proposed a web platform named ProbFAST for MDE analysis which uses Bayesian inference to identify key genes that are intuitively prioritized by means of probabilities. A simulated study revealed that our method gives a better performance when compared to other approaches and when applied to public expression data, we demonstrated its flexibility to obtain relevant genes biologically associated with normal and abnormal biological processes. Conclusions: ProbFAST is a free accessible web-based application that enables MDE analysis on a global scale. It offers an efficient methodological approach for MDE analysis of a set of genes that are turned on and off related to functional information during the evolution of a tumor or tissue differentiation. ProbFAST server can be accessed at http://gdm.fmrp.usp.br/probfast.

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Background: High-density tiling arrays and new sequencing technologies are generating rapidly increasing volumes of transcriptome and protein-DNA interaction data. Visualization and exploration of this data is critical to understanding the regulatory logic encoded in the genome by which the cell dynamically affects its physiology and interacts with its environment. Results: The Gaggle Genome Browser is a cross-platform desktop program for interactively visualizing high-throughput data in the context of the genome. Important features include dynamic panning and zooming, keyword search and open interoperability through the Gaggle framework. Users may bookmark locations on the genome with descriptive annotations and share these bookmarks with other users. The program handles large sets of user-generated data using an in-process database and leverages the facilities of SQL and the R environment for importing and manipulating data. A key aspect of the Gaggle Genome Browser is interoperability. By connecting to the Gaggle framework, the genome browser joins a suite of interconnected bioinformatics tools for analysis and visualization with connectivity to major public repositories of sequences, interactions and pathways. To this flexible environment for exploring and combining data, the Gaggle Genome Browser adds the ability to visualize diverse types of data in relation to its coordinates on the genome. Conclusions: Genomic coordinates function as a common key by which disparate biological data types can be related to one another. In the Gaggle Genome Browser, heterogeneous data are joined by their location on the genome to create information-rich visualizations yielding insight into genome organization, transcription and its regulation and, ultimately, a better understanding of the mechanisms that enable the cell to dynamically respond to its environment.

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Melanoma is a highly aggressive and therapy resistant tumor for which the identification of specific markers and therapeutic targets is highly desirable. We describe here the development and use of a bioinformatic pipeline tool, made publicly available under the name of EST2TSE, for the in silico detection of candidate genes with tissue-specific expression. Using this tool we mined the human EST (Expressed Sequence Tag) database for sequences derived exclusively from melanoma. We found 29 UniGene clusters of multiple ESTs with the potential to predict novel genes with melanoma-specific expression. Using a diverse panel of human tissues and cell lines, we validated the expression of a subset of three previously uncharacterized genes (clusters Hs.295012, Hs.518391, and Hs.559350) to be highly restricted to melanoma/melanocytes and named them RMEL1, 2 and 3, respectively. Expression analysis in nevi, primary melanomas, and metastatic melanomas revealed RMEL1 as a novel melanocytic lineage-specific gene up-regulated during melanoma development. RMEL2 expression was restricted to melanoma tissues and glioblastoma. RMEL3 showed strong up-regulation in nevi and was lost in metastatic tumors. Interestingly, we found correlations of RMEL2 and RMEL3 expression with improved patient outcome, suggesting tumor and/or metastasis suppressor functions for these genes. The three genes are composed of multiple exons and map to 2q12.2, 1q25.3, and 5q11.2, respectively. They are well conserved throughout primates, but not other genomes, and were predicted as having no coding potential, although primate-conserved and human-specific short ORFs could be found. Hairpin RNA secondary structures were also predicted. Concluding, this work offers new melanoma-specific genes for future validation as prognostic markers or as targets for the development of therapeutic strategies to treat melanoma.

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We consider a polling model with multiple stations, each with Poisson arrivals and a queue of infinite capacity. The service regime is exhaustive and there is Jacksonian feedback of served customers. What is new here is that when the server comes to a station it chooses the service rate and the feedback parameters at random; these remain valid during the whole stay of the server at that station. We give criteria for recurrence, transience and existence of the sth moment of the return time to the empty state for this model. This paper generalizes the model, when only two stations accept arriving jobs, which was considered in [Ann. Appl. Probab. 17 (2007) 1447-1473]. Our results are stated in terms of Lyapunov exponents for random matrices. From the recurrence criteria it can be seen that the polling model with parameter regeneration can exhibit the unusual phenomenon of null recurrence over a thick region of parameter space.

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This article presents a fieldbus simulation platform and its remote access interface that enables a wide range of experiments, where users can configure operation sequences and procedures typical of Foundation Fieldbus systems. The simulation system was developed using LabVIEW, with requisites of deterministic execution, and a course management work frame web server called Moodle. The results were obtained through three different evaluations: schedule table execution, simulator functionality and finally, simulator productivity and achievement. The evaluation attests that this new tool is feasible, and can be applied for fieldbus automation systems training purposes, considering the robustness and stability in tests and the positive feedback from users. (C) 2008 ISA. Published by Elsevier Ltd. All rights reserved.

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In this paper, we describe the Vannotea system - an application designed to enable collaborating groups to discuss and annotate collections of high quality images, video, audio or 3D objects. The system has been designed specifically to capture and share scholarly discourse and annotations about multimedia research data by teams of trusted colleagues within a research or academic environment. As such, it provides: authenticated access to a web browser search interface for discovering and retrieving media objects; a media replay window that can incorporate a variety of embedded plug-ins to render different scientific media formats; an annotation authoring, editing, searching and browsing tool; and session logging and replay capabilities. Annotations are personal remarks, interpretations, questions or references that can be attached to whole files, segments or regions. Vannotea enables annotations to be attached either synchronously (using jabber message passing and audio/video conferencing) or asynchronously and stand-alone. The annotations are stored on an Annotea server, extended for multimedia content. Their access, retrieval and re-use is controlled via Shibboleth identity management and XACML access policies.

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The electron transfer protein rubredoxin from Clostridium pasteurianum contains an Fe(S-Cys)(4) active site. Mutant proteins C9G, C9A, C42G and C42A, in which cysteine ligands are replaced by non-ligating Gly or Ala residues, have been expressed in Escherichia coli. The C42A protein expresses with a (Fe2S2)-S-III cluster in place. In contrast, the other proteins are isolated in colourless forms, although a (Fe2S2)-S-III cluster may be assembled in the C42G protein via incubation with Fe-III and sulfide. The four mutant proteins were isolated as stable mononuclear Hg-II forms which were converted to unstable mononuclear Fe-III preparations that contain both holo and apo protein. The Fe-III systems were characterized by metal analysis and mass spectrometry and by electronic, electron paramagnetic resonance, X-ray absorption and resonance Raman spectroscopies. The dominant Fe-III form in the C9A preparation is a Fe(S-Cys)(3)(OH) centre, similar to that observed previously in the C6S mutant protein. Related centres are present in the proteins NifU and IscU responsible for assembly and repair of iron-sulfur clusters in both prokaryotic and eukaryotic cells. In addition to Fe(S-Cys)(3)(OH) centres, the C9G, C42G and C42A preparations contain a second four-coordinate Fe-III form in which a ligand appears to be supplied by the protein chain. Electronic supplementary material to this paper can be obtained by using the Springer Link server located at http://dx.doi.org/10.1007/s00775-0020355-1.