Detecting distributed Denial-of-Service attacks and Flash Events

This thesis investigates and develops techniques for accurately detecting Internet-based Distributed Denial-of-Service (DDoS) Attacks where an adversary harnesses the power of thousands of compromised machines to disrupt the normal operations of a Web-service provider, resulting in significant down-time and financial losses. This thesis also develops methods to differentiate these attacks from similar-looking benign surges in web-traffic known as Flash Events (FEs). This thesis also addresses an intrinsic challenge in research associated with DDoS attacks, namely, the extreme scarcity of public domain datasets (due to legal and privacy issues) by developing techniques to realistically emulate DDoS attack and FE traffic.

Hybrid placemaking in the library : designing digital technology to enhance users’ on-site experience

This paper presents research findings and design strategies that illustrate how digital technology can be applied as a tool for hybrid placemaking in ways that would not be possible in purely digital or physical space. Digital technology has revolutionised the way people learn and gather new information. This trend has challenged the role of the library as a physical place, as well as the interplay of digital and physical aspects of the library. The paper provides an overview of how the penetration of digital technology into everyday life has affected the library as a place, both as designed by place makers, and, as perceived by library users. It then identifies a gap in current library research about the use of digital technology as a tool for placemaking, and reports results from a study of Gelatine – a custom built user check-in system that displays real-time user information on a set of public screens. Gelatine and its evaluation at The Edge, at State Library of Queensland illustrates how combining affordances of social, spatial and digital space can improve the connected learning experience among on-site visitors. Future design strategies involving gamifying the user experience in libraries are described based on Gelatine’s infrastructure. The presented design ideas and concepts are relevant for managers and designers of libraries as well as other informal, social learning environments.

Development of a large scale flexible LED display matrix for the screen industry

This project addresses the viability of lightweight, low power consumption, flexible, large format LED screens. The investigation encompasses all aspects of the electrical and mechanical design, individually and as a system, and achieves a successful full scale prototype. The prototype implements novel techniques to achieve large displacement colour aliasing, a purely passive thermal management solution, a rapid deployment system, individual seven bit LED current control with two way display communication, auto-configuration and complete signal redundancy, all of which are in direct response to industry needs.

Monocular vision based autonomous navigation for a cost-effective MAV in GPS-denied environments

In this paper, we present a monocular vision based autonomous navigation system for Micro Aerial Vehicles (MAVs) in GPS-denied environments. The major drawback of monocular systems is that the depth scale of the scene can not be determined without prior knowledge or other sensors. To address this problem, we minimize a cost function consisting of a drift-free altitude measurement and up-to-scale position estimate obtained using the visual sensor. We evaluate the scale estimator, state estimator and controller performance by comparing with ground truth data acquired using a motion capture system. All resources including source code, tutorial documentation and system models are available online.

Accountable-eHealth systems : the next step forward for privacy

eHealth systems promise enviable benefits and capabilities for healthcare delivery. However, the technologies that make these capabilities possible introduce undesirable drawbacks such as information security related threats, which need to be appropriately addressed. Lurking in these threats are information privacy concerns. Addressing them has proven to be difficult because they often conflict with information access requirements of healthcare providers. Therefore, it is important to achieve an appropriate balance between these requirements. We contend that information accountability (IA) can achieve this balance. In this paper, we introduce accountable-eHealth (AeH) systems, which are eHealth systems that utilise IA as a measure of information privacy. We discuss how AeH system protocols can successfully achieve the aforementioned balance of requirements. As a means of implementation feasibility, we compare characteristics of AeH systems with Australia’s Personally Controlled Electronic Health Record (PCEHR) sys-tem and identify similarities and highlight the differences and the impact those differences would have to the eHealth domain.

Investigating ways of seeing IT research : a tool for facilitating effective research partnerships?

Effective research partnerships, both intra- and interdisciplinary, as well as academy-industry partnerships, rely on shared understandings of particular aspects of the research endeavour. Research partnerships are essentially learning partnerships, if we accept the argument that research may be seen as learning at the collective level. This paper establishes the need to investigate information technology (IT) researchers' varying ways of seeing certain aspects of their research world, in order to assist the process of forging effective research partnerships. We analyse the importance of facilitating effective partnerships in IT research, discuss our plan for investigating the collective consciousness of IT researchers, and explain some of the strategies to be used in the investigation.

Driven to drive : designing gamification for a learner logbook smartphone application

Driving can be dangerous, especially for young and inexperienced drivers. To help address the issue of inexperience a gamified logbook application was developed for Learner drivers. The application aims to encourage learners to undertake a wider range of practice, while also making it easier to record their mandatory practice sessions. This paper reports on the design of this application, focusing on the effect that adding gamification can have on the usability and user experience of the application and the importance of playability testing for gamified systems. Two versions of the application were developed, one with game elements and one without game elements. This paper presents findings from a study that compares the user experience of these two versions of the application with twelve recent Learner drivers. Overall, participants reported that the gamified version was more engaging and motivating than the non-gamified version, however neither versions were preferred over the other. We theorise that this may have occurred due to a number of usability issues that arose, including an increased difficulty in learnability due to the added game elements. These design issues are important to address in future gamified system designs.

A combined method for mitigating sparsity problem in tag recommendation

Tag recommendation is a specific recommendation task for recommending metadata (tag) for a web resource (item) during user annotation process. In this context, sparsity problem refers to situation where tags need to be produced for items with few annotations or for user who tags few items. Most of the state of the art approaches in tag recommendation are rarely evaluated or perform poorly under this situation. This paper presents a combined method for mitigating sparsity problem in tag recommendation by mainly expanding and ranking candidate tags based on similar items’ tags and existing tag ontology. We evaluated the approach on two public social bookmarking datasets. The experiment results show better accuracy for recommendation in sparsity situation over several state of the art methods.

Nonlinear actuator fault detection for small-scale UAS

This paper presents a recursive strategy for online detection of actuator faults on a unmanned aerial system (UAS) subjected to accidental actuator faults. The proposed detection algorithm aims to provide a UAS with the capability of identifying and determining characteristics of actuator faults, offering necessary flight information for the design of fault-tolerant mechanism to compensate for the resultant side-effect when faults occur. The proposed fault detection strategy consists of a bank of unscented Kalman filters (UKFs) with each one detecting a specific type of actuator faults and estimating corresponding velocity and attitude information. Performance of the proposed method is evaluated using a typical nonlinear UAS model and it is demonstrated in simulations that our method is able to detect representative faults with a sufficient accuracy and acceptable time delay, and can be applied to the design of fault-tolerant flight control systems of UASs.

Intelligent tutoring system for learning PHP

This thesis investigates the possibility of using an adaptive tutoring system for beginning programming students. The work involved, designing, developing and evaluating such a system and showing that it was effective in increasing the students’ test scores. In doing so, Artificial Intelligence techniques were used to analyse PHP programs written by students and to provide feedback based on any specific errors made by them. Methods were also included to provide students with the next best exercise to suit their particular level of knowledge.

Scene invariant multi camera crowd counting

Automated crowd counting has become an active field of computer vision research in recent years. Existing approaches are scene-specific, as they are designed to operate in the single camera viewpoint that was used to train the system. Real world camera networks often span multiple viewpoints within a facility, including many regions of overlap. This paper proposes a novel scene invariant crowd counting algorithm that is designed to operate across multiple cameras. The approach uses camera calibration to normalise features between viewpoints and to compensate for regions of overlap. This compensation is performed by constructing an 'overlap map' which provides a measure of how much an object at one location is visible within other viewpoints. An investigation into the suitability of various feature types and regression models for scene invariant crowd counting is also conducted. The features investigated include object size, shape, edges and keypoints. The regression models evaluated include neural networks, K-nearest neighbours, linear and Gaussian process regresion. Our experiments demonstrate that accurate crowd counting was achieved across seven benchmark datasets, with optimal performance observed when all features were used and when Gaussian process regression was used. The combination of scene invariance and multi camera crowd counting is evaluated by training the system on footage obtained from the QUT camera network and testing it on three cameras from the PETS 2009 database. Highly accurate crowd counting was observed with a mean relative error of less than 10%. Our approach enables a pre-trained system to be deployed on a new environment without any additional training, bringing the field one step closer toward a 'plug and play' system.

Speaker attribution of Australian broadcast news data

Speaker attribution is the task of annotating a spoken audio archive based on speaker identities. This can be achieved using speaker diarization and speaker linking. In our previous work, we proposed an efficient attribution system, using complete-linkage clustering, for conducting attribution of large sets of two-speaker telephone data. In this paper, we build on our proposed approach to achieve a robust system, applicable to multiple recording domains. To do this, we first extend the diarization module of our system to accommodate multi-speaker (>2) recordings. We achieve this through using a robust cross-likelihood ratio (CLR) threshold stopping criterion for clustering, as opposed to the original stopping criterion of two speakers used for telephone data. We evaluate this baseline diarization module across a dataset of Australian broadcast news recordings, showing a significant lack of diarization accuracy without previous knowledge of the true number of speakers within a recording. We thus propose applying an additional pass of complete-linkage clustering to the diarization module, demonstrating an absolute improvement of 20% in diarization error rate (DER). We then evaluate our proposed multi-domain attribution system across the broadcast news data, demonstrating achievable attribution error rates (AER) as low as 17%.

The University of Queensland St Lucia campus 1.22 MW photovoltaic array

At the time of its official opening on 15 July 2011, The University of Queensland 1.22 MW array was the largest flat-panel PhotoVoltaic (PV) array in Australia. This PV array consists of over 5000 Trina Solar 240 Wp polycrystalline silicon PV modules installed across four rooftops at the St Lucia campus. Grid connection was achieved with 85 12.5 kW three phase and four 5 kW single phase grid connect inverters manufactured by Power-One. The site also includes one 8.4 kWp SolFocus concentrating solar 2 axis tracking PV array. Site wide monitoring and data logging of all DC, AC and environmental quantities will allow this array to be a rich source of research data. The site will also include a 200 kW 400 kWh zinc bromine energy storage system by Redflow, and associated power quality metering and monitoring. This paper presents highlights of the project feasibility study which included a site survey, shading analysis, and technology and triple bottom line assessment. A detailed description of the final technical implementation including discussion of alterative options considered is given. Finally, example initial data showing yield, trends and early example experimental results are presented.

Selection of energy storage system for a regenerative dynamic dynamometer

This paper presents a design technique of a fully regenerative dynamic dynamometer. It incorporates an energy storage system to absorb the energy variation due to dynamometer transients. This allows the minimum power electronics requirement at the grid to supply the losses. The simulation results of the full system over a driving cycle show the amount of energy required to complete a driving cycle, therefore the size of the energy storage system can be determined.

Brake system performance requirements of a lightweight electric/hybrid rear wheel drive vehicle

Investigates the braking performance requirements of the UltraCommuter, a lightweight series hybrid electric vehicle currently under development at the University of Queensland. With a predicted vehicle mass of 600 kg and two in-wheel motors each capable of 500 Nm of peak torque, decelerations up to 0.46 g are theoretically possible using purely regenerative braking. With 99% of braking demands less than 0.35 g, essentially all braking can be regenerative. The wheel motors have sufficient peak torque capability to lock the rear wheels in combination with front axle braking, eliminating the need for friction braking at the rear. Emergency braking levels approaching 1 g are achieved by supplementation with front disk brakes. This paper presents equations describing the peak front and rear axle braking forces which occur under straight line braking, including gradients. Conventionally, to guarantee stability, mechanical front/rear proportioning of braking effort ensures that the front axle locks first. In this application, all braking is initially regenerative at the rear, and an adaptive ''by-wire'' proportioning system presented ensures this stability requirement is still satisfied. Front wheel drive and all wheel drive systems are also discussed. Finally, peak and continuous performance measures, not commonly provided for friction brakes, are derived for the UltraCommuter's motor capability and range of operation.