An investigation into using SAP-PS as a multidimensional project control system (MPCS)

This paper investigates the effectiveness of using a corporate enterprise resource planning (ERP) system as a multi-dimensional project control system (MPCS) to monitor and control the work performed on projects, meet the needs and expectations of the project managers and support the requirements of other key stakeholders. A qualitative approach i.e. case study interviews and literature review accompanied by a quantitative computer system validation test approach was deployed. The results from this study suggest that the corporate ERP system is effective at monitoring and controlling the project stakeholder success criteria within a fully integrated environment. The system does however need to be setup and configured for the purpose of MPCS. This study contributes to the field by providing empirical evidence that corporate ERP systems are likely one of the only systems truly capable of solving the age old problem of how to expand the traditional singular dimensional approaches commonly used in project control, thus multiple control dimensions are integrated with each other and other business systems to form a multi-dimensional project control system.

Adaptive security for software systems

With continuously changing operational and business needs, system security is one of the key system capabilities that need to be updated as well. Most security engineering efforts focus on engineering security requirements of software systems at design time and existing adaptive security engineering efforts require complex design-time preparation. In this chapter we discuss the needs for adaptive software security, and key efforts in this area. We then introduce a new runtime adaptive security engineering approach, which enables adapting software security capabilities at runtime based on new security objectives, risks/threats, requirements as well as newly reported vulnerabilities. We categorize the source of adaptation in terms of manual adaptation (managed by end users), and automated adaption (automatically triggered by the platform). The new platform makes use of new ideas we built for vulnerability analysis, security engineering using aspect-oriented programming, and model-driven engineering techniques.

A comparative study at the logical level of centralised and distributed recovery in clusters

Cluster systems are becoming more prevalent in today’s computer society and users are beginning to request that these systems be reliable. Currently, most clusters have been designed to provide high performance at the cost of providing little to no reliability. To combat this, this report looks at how a recovery facility, based on either a centralised or distributed approach could be implemented into a cluster that is supported by a check pointing facility. This recovery facility can then recover failed user processes by using checkpoints of the processes that have been taken during failure free execution.

A risk analysis approach to critical information infrastructure protection

Critical Information Infrastructure (CII) has become a priority for all levels of management, It is one of the key components of efficient business and business continuity plans. There is a need for a new security methodology to deal with the new and unique attack threats and vulnerabilities associated with the new information technology security paradigm. Critical Information Infrastructure Protection - Risk Analysis Methodology
(ClIP-RAM), is a new security risk analysis method which copes with the shift from computer/information security to critical information infrastructure protection. This type of methodology is the next step toward handling information technology security risk at all levels from upper management information security down to firewall configurations. The paper will present the methodology of the new techniques and their application to critical information infrastructure protection. The associated advantages of this methodology will also be discussed.

Protecting web services from distributed denial of service attacks

The outcome of the research was the development of three network defence systems to protect corporate network infrastructure. The results showed that these defences were able to detect and filter around 94% of the DDoS attack traffic within a matter of seconds.

The effectiveness of graphical authentication

This research tested the effectiveness of a graphical approach to passwords. A field-experiment, in which graphical passwords were used by 185 subjects, helped to evaluate the approach. It was found that although graphical passwords were successfully used to authenticate useres, more work is required to ensure they are more usable.

A performance testing framework for digital forensic tools

This thesis surveys the latest development of digital forensic tools designed for anti-cybercrime purposes. It discusses the necessity of testing the digital forensics tools, and presents a novel testing framework. This new testing framework takes the viewpoint of software vendors rather than traditional software engineering approaches.

Self-aware virtualised autonomic self-management of non-dedicated clusters

This research aims at improving the accessibility of cluster computer systems by introducing autonomic self-management facilities incorporating; 1) resource discovery and self awareness, 2) virtualised resource pools, and 3) automated cluster membership and self configuration. These facilities simplify the user's programming workload and improve system usability.

Formalising a method for modelling critical infrastructure systems

This research delivers a multifaceted methodology that underpins a practical security analysis and system modelling framework applicable to critiquing modern critical infrastructure systems. The intent, to identify potential system security issues and gain operational insights that will contribute to improving system resilience, availability and ameliorate incident management responses for Australian critical infrastructure systems.

Reliable algorithms and attack detection schemes for network systems

Network and Information security and reliability is still a key issue in information technology. This thesis develops two algorithms to improve the reliability and stability of content delivery systems, and proposes three attack detection schemes with high effectiveness and accuracy in detecting network attacks.

Symbolic computation and perfect fluids in general relativity

Focuses on two areas within the field of general relativity. Firstly, the history and implications of the long-standing conjecture that general relativistic, shear-free perfect fluids which obey a barotropic equation of state p = p(w) such that w + p = 0, are either non-expanding or non-rotating. Secondly the application of the computer algebra system Maple to the area of tetrad formalisms in general relativity.

A microscopic competition model and its dynamics analysis on network attacks

Modeling network traffic has been a critical task in the development of Internet. Attacks and defense are prevalent in the current Internet. Traditional network models such as Poisson-related models do not consider the competition behaviors between the attack and defense parties. In this paper, we present a microscopic competition model to analyze the dynamics among the nodes, benign or malicious, connected to a router, which compete for the bandwidth. The dynamics analysis demonstrates that the model can well describe the competition behavior among normal users and attackers. Based on this model, an anomaly attack detection method is presented. The method is based on the adaptive resonance theory, which is used to learn the model by normal traffic data. The evaluation shows that it can effectively detect the network attacks.

Using relationship-building in event profiling for digital forensic investigations

In a forensic investigation, computer profiling is used to capture evidence and to examine events surrounding a crime. A rapid increase in the last few years in the volume of data needing examination has led to an urgent need for automation of profiling. In this paper, we present an efficient, automated event profiling approach to a forensic investigation for a computer system and its activity over a fixed time period. While research in this area has adopted a number of methods, we extend and adapt work of Marrington et al. based on a simple relational model. Our work differs from theirs in a number of ways: our object set (files, applications etc.) can be enlarged or diminished repeatedly during the analysis; the transitive relation between objects is used sparingly in our work as it tends to increase the set of objects requiring investigative attention; our objective is to reduce the volume of data to be analyzed rather than extending it. We present a substantial case study to illuminate the theory presented here. The case study also illustrates how a simple visual representation of the analysis could be used to assist a forensic team.