An investigation into system security requirements and implementation in an Application Service Provider (ASP) environment

Although the ASP model has been around for over a decade, it has not achieved the expected high level of market uptake. This research project examines the past and present state of ASP adoption and identifies security as a primary factor influencing the uptake of the model. The early chapters of this document examine the ASP model and ASP security in particular. Specifically, the literature and technology review chapter analyses ASP literature, security technologies and best practices with respect to system security in general. Based on this investigation, a prototype to illustrate the range and types of technologies that encompass a security framework was developed and is described in detail. The latter chapters of this document evaluate the practical implementation of system security in an ASP environment. Finally, this document outlines the research outputs, including the conclusions drawn and recommendations with respect to system security in an ASP environment. The primary research output is the recommendation that by following best practices with respect to security, an ASP application can provide the same level of security one would expect from any other n-tier client-server application. In addition, a security evaluation matrix, which could be used to evaluate not only the security of ASP applications but the security of any n-tier application, was developed by the author. This thesis shows that perceptions with regard to fears of inadequate security of ASP solutions and solution data are misguided. Finally, based on the research conducted, the author recommends that ASP solutions should be developed and deployed on tried, tested and trusted infrastructure. Existing Application Programming Interfaces (APIs) should be used where possible and security best practices should be adhered to where feasible.

Application of multivariate statistical process control to fuel cell manufacturing

Univariate statistical control charts, such as the Shewhart chart, do not satisfy the requirements for process monitoring on a high volume automated fuel cell manufacturing line. This is because of the number of variables that require monitoring. The risk of elevated false alarms, due to the nature of the process being high volume, can present problems if univariate methods are used. Multivariate statistical methods are discussed as an alternative for process monitoring and control. The research presented is conducted on a manufacturing line which evaluates the performance of a fuel cell. It has three stages of production assembly that contribute to the final end product performance. The product performance is assessed by power and energy measurements, taken at various time points throughout the discharge testing of the fuel cell. The literature review performed on these multivariate techniques are evaluated using individual and batch observations. Modern techniques using multivariate control charts on Hotellings T2 are compared to other multivariate methods, such as Principal Components Analysis (PCA). The latter, PCA, was identified as the most suitable method. Control charts such as, scores, T2 and DModX charts, are constructed from the PCA model. Diagnostic procedures, using Contribution plots, for out of control points that are detected using these control charts, are also discussed. These plots enable the investigator to perform root cause analysis. Multivariate batch techniques are compared to individual observations typically seen on continuous processes. Recommendations, for the introduction of multivariate techniques that would be appropriate for most high volume processes, are also covered.