Date of Award

2017

Document Type

Thesis - ECU Access Only

Publisher

Edith Cowan University

Degree Name

Doctor of Philosophy

School

School of Science

First Supervisor

Dr Jitian Xiao

Second Supervisor

Dr Zubair Baig

Abstract

With the evolution of networking technology, mobile devices and E-Commerce have played a more pervasive role in enterprise production environment. Computer networks have been adopted as an indispensable part of an enterprise’s operations, resource planning and customer relation management, and so on. The evolved computer networks enable more flexible and innovative business tools such as wireless internet banking and mobile advertising. At the same time, the increasing network scale and data volume have introduced new challenges for enterprises. The increased volume of enterprise data has become more difficult to manage. The increased value of information is making the enterprise information systems bigger targets for hackers. The industry needs more efficient analytic systems that not only organize the essential processes and procedures to assess vast amount of data, but also help enterprise to make decisions on how to secure their information systems and business operations.

Recent dramatic increases in the rate of data creation have left enterprises grappling with the complexities of big data. Wisely utilizing enterprise data has become a significant part of enhancing the enterprise productivity. Proper processes with the data from various sources are expected to increase profitability and the overall value of enterprise. Although a lot of existing research have exploited strategies to deal with the new challenges faced by modern enterprise information systems, none of them constitutes a widely acceptable solution. In addition, various implementations of distribution computing techniques have been done in solving enterprise security and operational issues. However, those implementations are mostly ad hoc application for the specific projects. Lacking of a universal framework, it requires higher investigation cost before/during implementing the projects.

This research aims to create a better solution with the merits of incorporating distributed computing with information fusion to facilitate the enterprise security and operation. Distributed computing is an agile solution for handling such a large amount of data. Information fusion can be an effective vehicle over distributed environments for the automated generation of analysis results and business strategies from the overwhelming information haystacks. This research combines these methodologies to constitute a series of innovative solutions for the core issues in the big data era, including the information overload and analytic complexity. As a result, enterprise can solve the akin issues with high cost-efficiency and high performance with the developed models. The techniques developed in the research are conducive to the security assessment of large enterprise information systems, and operational data analysis for improving business performance. These techniques include integrated analytic methods on the platitude transactions of security logs and business activities. The frameworks developed in the research utilize the innovative concepts to provide remedies for various emerging enterprise issues including enhanced vulnerability identification and business pattern discovery. The issues considered in the framework development include a cloud-based wireless network defence strategy, a big data mobile application assessment strategy, a big data customer behaviour analysis strategy, cloud-based multi-language support, and PhD Thesis Page vii Hongye Zhong (John) big data health data analytics. Along with the frameworks, the research forms guidelines that are integrated with the developed techniques and frameworks for implementing the systems to address the industrial issues on enterprise security and operations.

Based on the guidelines, prototype systems have been constructed in the experiments for evaluation and illustration purposes. Through the experiments, the performance of the developed models has been verified. It is proven that the hybrid model of distribution computing and information fusion can provide a flexible and efficient solution to enterprise networking and software security. In addition, evidence shows that the cloud-based data fusion model can be an assistive tool for enterprises on customer information analytics.

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