Towards secure web services: Performance analysis, decision making and steganography approaches

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Web services provide a platform neutral and programming language independent technology that supports interoperable machine-to-machine interaction over a network. Clients and other systems interact with Web services using a standardised XML messaging system, such as the Simple Object Access Protocol (SOAP), typically conveyed using HTTP with an XML serialisation in conjunction with other related Web standards. Nevertheless, the idea of applications from different parties communicating together raises a security threat. The challenge of Web services security is to understand and consider the risks of securing a Web-based service depending on the existing security techniques and simultaneously follow evolving standards in order to fill the gap in Web services security. However, the performance of the security mechanisms is fraught with concerns due to additional security contents in SOAP messages, the higher number of message exchanges to establish trust, as well as the extra CPU time to process these additions. As the interaction between service providers and requesters occurs via XML-based SOAP messages, securing Web services tends to make these messages longer than they would be otherwise and consequently requires interpretation by XML parsers on both sides, which reduces the performance of Web services. The work described in this thesis can be broadly divided into three parts, the first of which is studying and comparing the performance of various security profiles applied on a Web service tested with different initial message sizes. The second part proposes a multi-criteria decision making framework to aid Web services developers and architects in selecting the best suited security profile that satisfies the different requirements of a given application during the development process in a systematic, manageable, and effective way. The proposed framework, based on the Analytical Hierarchy Process (AHP) approach, incorporates not only the security requirements, but also the performance considerations as well as the configuration constraints of these security profiles. The framework is then validated and evaluated using a scenario-driven approach to demonstrate situations where the decision making framework is used to make informed decisions to rank various security profiles in order to select the most suitable one for each scenario. Finally, the last part of this thesis develops a novel steganography method to be used for SOAP messages within Web services environments. This method is based on changing the order of XML elements according to a secret message. This method has a high imperceptibility; it leaves almost no trail because it uses the communication protocol as a cover medium, and keeps the structure and size of the SOAP message intact. The method is empirically validated using a feasible scenario so as to indicate its utility and value

Cloud adoption decision support for SMEs Using Analytical Hierarchy Process (AHP)

For a successful cloud adoption, decision makers need to consider numerous aspects before deciding to adopt cloud infrastructure. In this paper, we propose a framework to support cloud adoption decisions for SMEs in Tamil Nadu (India) using the established principles of Analytical Hierarchy Process (AHP). This study is focused on SMEs in Tamil Nadu, one of the constituent states of the Indian Union. This paper reports on the findings of applying AHP to real data collected from decision makers and demonstrates its usefulness as a decision support tool for SMEs in Tamil Nad

Information Retrieval Performance Enhancement Using The Average Standard Estimator And The Multi-criteria Decision Weighted Set

Information retrieval is much more challenging than traditional small document collection retrieval. The main difference is the importance of correlations between related concepts in complex data structures. These structures have been studied by several information retrieval systems. This research began by performing a comprehensive review and comparison of several techniques of matrix dimensionality estimation and their respective effects on enhancing retrieval performance using singular value decomposition and latent semantic analysis. Two novel techniques have been introduced in this research to enhance intrinsic dimensionality estimation, the Multi-criteria Decision Weighted model to estimate matrix intrinsic dimensionality for large document collections and the Average Standard Estimator (ASE) for estimating data intrinsic dimensionality based on the singular value decomposition (SVD). ASE estimates the level of significance for singular values resulting from the singular value decomposition. ASE assumes that those variables with deep relations have sufficient correlation and that only those relationships with high singular values are significant and should be maintained. Experimental results over all possible dimensions indicated that ASE improved matrix intrinsic dimensionality estimation by including the effect of both singular values magnitude of decrease and random noise distracters. Analysis based on selected performance measures indicates that for each document collection there is a region of lower dimensionalities associated with improved retrieval performance. However, there was clear disagreement between the various performance measures on the model associated with best performance. The introduction of the multi-weighted model and Analytical Hierarchy Processing (AHP) analysis helped in ranking dimensionality estimation techniques and facilitates satisfying overall model goals by leveraging contradicting constrains and satisfying information retrieval priorities. ASE provided the best estimate for MEDLINE intrinsic dimensionality among all other dimensionality estimation techniques, and further, ASE improved precision and relative relevance by 10.2% and 7.4% respectively. AHP analysis indicates that ASE and the weighted model ranked the best among other methods with 30.3% and 20.3% in satisfying overall model goals in MEDLINE and 22.6% and 25.1% for CRANFIELD. The weighted model improved MEDLINE relative relevance by 4.4%, while the scree plot, weighted model, and ASE provided better estimation of data intrinsic dimensionality for CRANFIELD collection than Kaiser-Guttman and Percentage of variance. ASE dimensionality estimation technique provided a better estimation of CISI intrinsic dimensionality than all other tested methods since all methods except ASE tend to underestimate CISI document collection intrinsic dimensionality. ASE improved CISI average relative relevance and average search length by 28.4% and 22.0% respectively. This research provided evidence supporting a system using a weighted multi-criteria performance evaluation technique resulting in better overall performance than a single criteria ranking model. Thus, the weighted multi-criteria model with dimensionality reduction provides a more efficient implementation for information retrieval than using a full rank model

Deep Learning para BigData

We live in a world where data is becoming increasingly valuable and increasingly abundant in volume. Every company produces data, be it from sales, sensors, and various other sources. Since the dawn of the smartphone, virtually every person in the world is connected to the internet and contributes to data generation. Social networks are big contributors to this Big Data boom. How do we extract insight from such a rich data environment? Is Deep Learning capable of circumventing Big Data’s challenges? This is what we intend to understand. To reach a conclusion, Social Network data is used as a case study for predicting sentiment changes in the Stock Market. The objective of this dissertation is to develop a computational study and analyse its performance. The outputs will contribute to understand Deep Learning’s usage with Big Data and how it acts in Sentiment analysis.Vivemos num mundo onde dados são cada vez mais valiosos e abundantes. Todas as empresas produzem dados, sejam eles provenientes de valores de vendas, parâmetros de sensores bem como de outras diversas fontes. Desde que os smartphones se tornaram pessoais, o mundo tornou-se mais conectado, já que virtualmente todas as pessoas passaram a ter a internet na ponta dos dedos. Esta explosão tecnológica foi acompanhada por uma explosão de dados. As redes sociais têm um grande contributo para a quantidade de dados produzida. Mas como se analisam estes dados? Será que Deep Learning poderá dar a volta aos desafios que Big Data traz inerentemente? É isso se pretende perceber. Para chegar a uma conclusão, foi utilizado um caso de estudo de redes sociais para previsão de alterações nas ações de mercados financeiros relacionadas com as opiniões dos utilizadores destas. O objetivo desta dissertação é o desenvolvimento de um estudo computacional e a análise da sua performance. Os resultados contribuirão para entender o uso de Deep Learning com Big Data, com especial foco em análise de sentimento. The objective of this dissertation is to develop a computational study and analyse its performance. The outputs will contribute to understand Deep Learning’s usage with Big Data and how it acts in Sentiment analysis

An integrated system to design machine layouts for modular special purpose machines

This thesis introduces the development of an integrated system for the design of layouts for special purpose machines (SPMs). SPMs are capable of performing several machining operations (such as drilling, milling, and tapping) at the same time. They consist of elements that can be arranged in different layouts. Whilst this is a unique feature that makes SPMs modular, a high level of knowledge and experience is required to rearrange the SPM elements in different configurations, and also to select appropriate SPM elements when product demand changes and new layouts are required. In this research, an integrated system for SPM layout design was developed by considering the following components: an expert system tool, an assembly modelling approach for SPM layouts, an artificial intelligence tool, and a CAD design environment. SolidWorks was used as the 3D CAD environment. VisiRule was used as the expert system tool to make decisions about the selection of SPM elements. An assembly modelling approach was developed with an SPM database using a linked list structure and assembly relationships graph. A case-based reasoning (CBR) approach was developed and applied to automate the selection of SPM layouts. These components were integrated using application programing interface (API) features and Visual Basic programming language. The outcome of the application of the novel approach that was developed in this thesis is reducing the steps for the assembly process of the SPM elements and reducing the time for designing SPM layouts. As a result, only one step is required to assemble any two SPM elements and the time for the selection process of SPM layouts is reduced by approximately 75% compared to the traditional processes. The integrated system developed in this thesis will help engineers in design and manufacturing fields to design SPM layouts in a more time-effective manner

Production and Logistics Systems Improvements - Biim Ultrasound AS

A crucial aspect of the supply chain network design process is deciding on optimal locations to situate new facilities. Facility location decisions rely on many factors, some of which might be conflicting with each other. The decision factors can be either quantitative or qualitative, thus a brute-force prioritization of one over another could be detrimental overall. To ensure the efficacy of the selection process, decision makers must consider both the quantitative and qualitative factors in tandem. Some of the common methods employed in the literature by organizations to facilitate their decision-making process include: optimization models and algorithms, decision support systems and computerized analytics tools. To this end, this thesis proposes a hybrid Multi-Criteria Decision Making (MCDM) model to aid the selection of an optimal location that suits the strategic fit of an organization. The proposed model integrates the Analytic Hierarchy Process (AHP) methodology for Multi-Attribute Decision Making (MADM) with Mixed Integer Programming (MIP). The solution is modeled and implemented with the AIMMS modeling language as well as the Gurobi Optimization tool in Python. This thesis work is based on a case study from Biim Ultrasound

Testes End to End em Microserviços

The microservices architecture is a recent trend in the software engineering community, with the number of research articles in the field increasing, and more companies adopting the architectural style every year. However, the testing aspect of this architecture can sometimes be overlooked, with a lack of guidelines for its execution. Also, microservices testing introduce a lot of different challenges that are not faced when following a monolithic architecture. This work aims to fill some gaps in current microservices testing research by providing a study of five existing service virtualization tools, implementing them in a company system and extracting the results of the tool properties identified through a survey delivered to a convenience sample of software development experts. Finally, the mentioned experts in the microservices field validated the results of the research and the tool identified as the best and provided insights regarding the value of this work.A arquitetura de micros serviços é uma tendência recente na comunidade de engenharia de software, com o número de artigos na área a aumentar e mais empresas a adotar o estilo arquitetónico a cada ano. No entanto, a área dos testes end-to-end desta arquitetura pode às vezes ser esquecido. Além disso, os testes de micros serviços apresentam muitos desafios diferentes que não são enfrentados ao seguir uma arquitetura monolítica. Este trabalho visa preencher algumas lacunas na pesquisa de teste de micros serviços atuais, fornecendo um estudo de cinco ferramentas de virtualização de serviço existentes, implementando-as num sistema empresarial e extraindo os resultados das propriedades da ferramenta identificadas por meio de um questionário entregue a uma amostra de conveniência de especialistas em desenvolvimento de software. Por fim, os citados especialistas na área de micros serviços validaram os resultados da pesquisa e a ferramenta identificada como a melhor e forneceram a sua visão geral sobre o valor deste trabalho

Design rules and guidelines for generic condition-based maintenance software's Graphic User Interface

The task of selecting and developing a method of Human Computer Interaction (HCI) for a Condition Based Maintenance (CBM) system, is investigated in this thesis. Efficiently and accurately communicating machinery health information extracted from Condition Monitoring (CM) equipment, to aid and assist plant and machinery maintenance decisions, is the crux of the problem being researched. Challenges facing this research include: the multitude of different CM techniques, developed for measuring different component and machinery condition parameters; the multitude of different methods of HCI; and the multitude of different ways of communicating machinery health conditions to CBM practitioners. Each challenge will be considered whilst pursuing the objective of identifying a generic set of design and development principles, applicable to the design and development of a CBM system's Human Machine Interface (HMI). [Continues.

Towards secure web services : performance analysis, decision making and steganography approaches

Web services provide a platform neutral and programming language independent technology that supports interoperable machine-to-machine interaction over a network. Clients and other systems interact with Web services using a standardised XML messaging system, such as the Simple Object Access Protocol (SOAP), typically conveyed using HTTP with an XML serialisation in conjunction with other related Web standards. Nevertheless, the idea of applications from different parties communicating together raises a security threat. The challenge of Web services security is to understand and consider the risks of securing a Web-based service depending on the existing security techniques and simultaneously follow evolving standards in order to fill the gap in Web services security. However, the performance of the security mechanisms is fraught with concerns due to additional security contents in SOAP messages, the higher number of message exchanges to establish trust, as well as the extra CPU time to process these additions. As the interaction between service providers and requesters occurs via XML-based SOAP messages, securing Web services tends to make these messages longer than they would be otherwise and consequently requires interpretation by XML parsers on both sides, which reduces the performance of Web services. The work described in this thesis can be broadly divided into three parts, the first of which is studying and comparing the performance of various security profiles applied on a Web service tested with different initial message sizes. The second part proposes a multi-criteria decision making framework to aid Web services developers and architects in selecting the best suited security profile that satisfies the different requirements of a given application during the development process in a systematic, manageable, and effective way. The proposed framework, based on the Analytical Hierarchy Process (AHP) approach, incorporates not only the security requirements, but also the performance considerations as well as the configuration constraints of these security profiles. The framework is then validated and evaluated using a scenario-driven approach to demonstrate situations where the decision making framework is used to make informed decisions to rank various security profiles in order to select the most suitable one for each scenario. Finally, the last part of this thesis develops a novel steganography method to be used for SOAP messages within Web services environments. This method is based on changing the order of XML elements according to a secret message. This method has a high imperceptibility; it leaves almost no trail because it uses the communication protocol as a cover medium, and keeps the structure and size of the SOAP message intact. The method is empirically validated using a feasible scenario so as to indicate its utility and value.EThOS - Electronic Theses Online ServiceGBUnited Kingdo