Use of IP addresses for high rate flooding attack detection

High-rate flooding attacks (aka Distributed Denial of Service or DDoS attacks) continue to constitute a pernicious threat within the Internet domain. In this work we demonstrate how using packet source IP addresses coupled with a change-point analysis of the rate of arrival of new IP addresses may be sufficient to detect the onset of a high-rate flooding attack. Importantly, minimizing the number of features to be examined, directly addresses the issue of scalability of the detection process to higher network speeds. Using a proof of concept implementation we have shown how pre-onset IP addresses can be efficiently represented using a bit vector and used to modify a “white list” filter in a firewall as part of the mitigation strategy.

A hidden Markov model and relative entropy rate approach to vision-based dim target detection for UAV sense-and-avoid

Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.

Towards a game theoretic authorisation model

Authorised users (insiders) are behind the majority of security incidents with high financial impacts. Because authorisation is the process of controlling users’ access to resources, improving authorisation techniques may mitigate the insider threat. Current approaches to authorisation suffer from the assumption that users will (can) not depart from the expected behaviour implicit in the authorisation policy. In reality however, users can and do depart from the canonical behaviour. This paper argues that the conflict of interest between insiders and authorisation mechanisms is analogous to the subset of problems formally studied in the field of game theory. It proposes a game theoretic authorisation model that can ensure users’ potential misuse of a resource is explicitly considered while making an authorisation decision. The resulting authorisation model is dynamic in the sense that its access decisions vary according to the changes in explicit factors that influence the cost of misuse for both the authorisation mechanism and the insider.

Reliability analysis with suspended items

Reliability analysis has several important engineering applications. Designers and operators of equipment are often interested in the probability of the equipment operating successfully to a given age - this probability is known as the equipment's reliability at that age. Reliability information is also important to those charged with maintaining an item of equipment, as it enables them to model and evaluate alternative maintenance policies for the equipment. In each case, information on failures and survivals of a typical sample of items is used to estimate the required probabilities as a function of the item's age, this process being one of many applications of the statistical techniques known as distribution fitting. In most engineering applications, the estimation procedure must deal with samples containing survivors (suspensions or censorings); this thesis focuses on several graphical estimation methods that are widely used for analysing such samples. Although these methods have been current for many years, they share a common shortcoming: none of them is continuously sensitive to changes in the ages of the suspensions, and we show that the resulting reliability estimates are therefore more pessimistic than necessary. We use a simple example to show that the existing graphical methods take no account of any service recorded by suspensions beyond their respective previous failures, and that this behaviour is inconsistent with one's intuitive expectations. In the course of this thesis, we demonstrate that the existing methods are only justified under restricted conditions. We present several improved methods and demonstrate that each of them overcomes the problem described above, while reducing to one of the existing methods where this is justified. Each of the improved methods thus provides a realistic set of reliability estimates for general (unrestricted) censored samples. Several related variations on these improved methods are also presented and justified. - i

Modelling of inflatable rescue boats (IRBs) in surf conditions to reduce injuries

The Inflatable Rescue Boat (IRB) is arguably the most effective rescue tool used by the Australian surf lifesavers. The exceptional features of high mobility and rapid response have enabled it to become an icon on Australia's popular beaches. However, the IRB's extensive use within an environment that is as rugged as it is spectacular, has led it to become a danger to those who risk their lives to save others. Epidemiological research revealed lower limb injuries to be predominant, particularly the right leg. The common types of injuries were fractures and dislocations, as well as muscle or ligament strains and tears. The concern expressed by Surf Life Saving Queensland (SLSQ) and Surf Life Saving Australia (SLSA) led to a biomechanical investigation into this unique and relatively unresearched field. The aim of the research was to identify the causes of injury and propose processes that may reduce the instances and severity of injury to surf lifesavers during IRB operation. Following a review of related research, a design analysis of the craft was undertaken as an introduction to the craft, its design and uses. The mechanical characteristics of the vessel were then evaluated and the accelerations applied to the crew in the IRB were established through field tests. The data were then combined and modelled in the 3-D mathematical modelling and simulation package, MADYMO. A tool was created to compare various scenarios of boat design and methods of operation to determine possible mechanisms to reduce injuries. The results of this study showed that under simulated wave loading the boats flex around a pivot point determined by the position of the hinge in the floorboard. It was also found that the accelerations experienced by the crew exhibited similar characteristics to road vehicle accidents. Staged simulations indicated the attributes of an optimum foam in terms of thickness and density. Likewise, modelling of the boat and crew produced simulations that predicted realistic crew response to tested variables. Unfortunately, the observed lack of adherence to the SLSA footstrap Standard has impeded successful epidemiological and modelling outcomes. If uniformity of boat setup can be assured then epidemiological studies will be able to highlight the influence of implementing changes to the boat design. In conclusion, the research provided a tool to successfully link the epidemiology and injury diagnosis to the mechanical engineering design through the use of biomechanics. This was a novel application of the mathematical modelling software MADYMO. Other craft can also be investigated in this manner to provide solutions to the problem identified and therefore reduce risk of injury for the operators.

The peer-to-patent initiative : revitalizing patent examination with peer review

Every day we hear someone complain that this or that patent should not have been granted. People complain that the patent system is now a threat to existing business and innovation be- cause the patent office grants with alarming regularity patents for inventions that are neither novel nor non-obvious. People argue that the patent office cannot keep up with the job of examining the backlog of hundreds of thousands of patents and that, even if it could, the large volumes of prior art literature that need to be considered each time a patent application is received make the decision as to whether a patent should be granted or not a treacherous one.

Application of micro CT and computation modeling in bone tissue engineering

Computer aided technologies, medical imaging, and rapid prototyping has created new possibilities in biomedical engineering. The systematic variation of scaffold architecture as well as the mineralization inside a scaffold/bone construct can be studied using computer imaging technology and CAD/CAM and micro computed tomography (CT). In this paper, the potential of combining these technologies has been exploited in the study of scaffolds and osteochondral repair. Porosity, surface area per unit volume and the degree of interconnectivity were evaluated through imaging and computer aided manipulation of the scaffold scan data. For the osteochondral model, the spatial distribution and the degree of bone regeneration were evaluated. In this study the versatility of two softwares Mimics (Materialize), CTan and 3D realistic visualization (Skyscan) were assessed, too.

Ramifications of development projects deemed “state significant”

Purpose, Design/methodology / approach The acknowledgement of state significance in relation to development projects can result in special treatment by regulatory authorities, particularly in terms of environmental compliance and certain economic and other government support measures. However, defining just what constitutes a “significant project”, or a project of “state significance”, varies considerably between Australian states. In terms of establishing threshold levels, in Queensland there is even less clarity. Despite this lack of definition, the implications of “state significance” can nevertheless be considerable. For example, in Queensland if the Coordinator-General declares a project to be a “significant project” under the State Development and Public Works Organisation Act 1971, the environmental impact assessment process may become more streamlined – potentially circumventing certain provisions under The Integrated Planning Act 1997. If the project is not large enough to be so deemed, an extractive resource under the State Planning Policy 2/07 - Protection of Extractive Resources 2007 may be considered to be of State or regional significance and subsequently designated as a “Key Resource Area”. As a consequence, such a project is afforded some measure of resource protection but remains subject to the normal assessment process under the Integrated Development Assessment System, as well as the usual requirements of the vegetation management codes, and other regulations. Findings (Originality/value) & Research limitations / implications This paper explores the various meanings of “state significance” in Queensland and the ramifications for development projects in that state. It argues for a streamlining of the assessment process in order to avoid or minimise constraints acting on the state’s development. In so doing, it questions the existence of a strategic threat to the delivery of an already over-stretched infrastructure program.

Evaluation of risk factors leading to cost overrun in delivery of highway construction projects

Accurate owner budget estimates are critical to the initial decision-to-build process for highway construction projects. However, transportation projects have historically experienced significant construction cost overruns from the time the decision to build has been taken by the owner. This paper addresses the problem of why highway projects overrun their predicted costs. It identifies the owner risk variables that contribute to significant cost overrun and then uses factor analysis, expert elicitation, and the nominal group technique to establish groups of importance ranked owner risks. Stepwise multivariate regression analysis is also used to investigate any correlation of the percentage of cost overrun with risks, together with attributes such as highway project type, indexed cost, geographics location, and project delivery method. The research results indicate a correlation between the reciprocal of project budgets size and percentage cost overrun. This can be useful for owners in determining more realistic decision-to-build highway budget estimates by taking into account the economies of scale associated with larger projects.

Information sharing in the 21st century : progress and challenges

With the increasing threat of cyber and other attacks on critical infrastructure, governments throughout the world have been organizing industry to share information on possible threats. In Australia the Office of the Attorney General has formed Trusted Information Sharing Networks (TISN) for the various critical industries such as banking and electricity. Currently the majority of information for a TISN is shared at physical meetings. To meet cyber threats there are clearly limitations to physical meetings. Many of these limitations can be overcome by the creation of a virtual information sharing network (VISN). However there are many challenges to overcome in the design of a VISN both from a policy and technical viewpoint. We shall discuss some of these challenges in this talk.

The use of phase in complex spectrum subtraction for robust speech recognition

In this paper we propose a new method for utilising phase information by complementing it with traditional magnitude-only spectral subtraction speech enhancement through Complex Spectrum Subtraction (CSS). The proposed approach has the following advantages over traditional magnitude-only spectral subtraction: (a) it introduces complementary information to the enhancement algorithm; (b) it reduces the total number of algorithmic parameters, and; (c) is designed for improving clean speech magnitude spectra and is therefore suitable for both automatic speech recognition (ASR) and speech perception applications. Oracle-based ASR experiments verify this approach, showing an average of 20% relative word accuracy improvements when accurate estimates of the phase spectrum are available. Based on sinusoidal analysis and assuming stationarity between observations (which is shown to be better approximated as the frame rate is increased), this paper also proposes a novel method for acquiring the phase information called Phase Estimation via Delay Projection (PEDEP). Further oracle ASR experiments validate the potential for the proposed PEDEP technique in ideal conditions. Realistic implementation of CSS with PEDEP shows performance comparable to state of the art spectral subtraction techniques in a range of 15-20 dB signal-to-noise ratio environments. These results clearly demonstrate the potential for using phase spectra in spectral subtractive enhancement applications, and at the same time highlight the need for deriving more accurate phase estimates in a wider range of noise conditions.

Vulnerability factors for disaster-induced child post-traumatic stress disorder : the case for low family resilience and previous mental illness

Objective: The aim of the present study was to investigate whether parent report of family resilience predicted children’s disaster-induced post-traumatic stress disorder (PTSD) and general emotional symptoms, independent of a broad range of variables including event-related factors, previous child mental illness and social connectedness. ---------- Methods: A total of 568 children (mean age = 10.2 years, SD = 1.3) who attended public primary schools, were screened 3 months after Cyclone Larry devastated the Innisfail region of North Queensland. Measures included parent report on the Family Resilience Measure and Strengths and Difficulties Questionnaire (SDQ)–emotional subscale and child report on the PTSD Reaction Index, measures of event exposure and social connectedness. ---------- Results: Sixty-four students (11.3%) were in the severe–very severe PTSD category and 53 families (28.6%) scored in the poor family resilience range. A lower family resilience score was associated with child emotional problems on the SDQ and longer duration of previous child mental health difficulties, but not disaster-induced child PTSD or child threat perception on either bivariate analysis, or as a main or moderator variable on multivariate analysis (main effect: adjusted odds ratio (ORadj) = 0.57, 95% confidence interval (CI) = 0.13–2.44). Similarly, previous mental illness was not a significant predictor of child PTSD in the multivariate model (ORadj = 0.75, 95%CI = 0.16–3.61). ---------- Conclusion: In this post-disaster sample children with existing mental health problems and those of low-resilience families were not at elevated risk of PTSD. The possibility that the aetiological model of disaster-induced child PTSD may differ from usual child and adolescent conceptualizations is discussed.

Metal Contaminants in Leachate from Sanitary Landfills

The uncontrolled disposal of solid wastes poses an immediate threat to public health and a long term threat to the environmental well being of future generations. Solid waste is waste resulting from human activities that is solid and unwanted (Peavy et al., 1985). If unmanaged, dumped solid wastes generate liquid and gaseous emissions that are detrimental to the environment. This can lead to a serious form of contamination known as metal contamination, which poses a risk to human health and ecosystems. For example, some heavy metals (cadmium, chromium compounds, and nickel tetracarbonyl) are known to be highly toxic, and are aggressive at elevated concentrations. Iron, copper, and manganese can cause staining, and aluminium causes depositions and discolorations. In addition, calcium and magnesium cause hardness in water causing scale deposition and scum formation. Though not a metal but a metalloid, arsenic is poisonous at relatively high concentrations and when diluted at low concentrations causes skin cancer. Normally, metal contaminants are found in a dissolved form in the liquid percolating through landfills. Because average metal concentrations from full-scale landfills, test cells, and laboratory studies have tended to be generally low, metal contamination originating from landfills is not generally considered a major concern (Kjeldsen et al., 2002; Christensen et al., 1999). However, a number of factors make it necessary to take a closer look at metal contaminants from landfills. One of these factors relates to variability. Landfill leachate can have different qualities depending on the weather and operating conditions. Therefore, at one moment in time, metal contaminant concentrations may be quite low, but at a later time these concentrations could be quite high. Also, these conditions relate to the amount of leachate that is being generated. Another factor is biodiversity. It cannot be assumed that a particular metal contaminant is harmless to flora and fauna (including micro organisms) just because it is harmless to human health. This has significant implications for ecosystems and the environment. Finally, there is the moral factor. Because uncertainty surrounds the potential effects of metal contamination, it is appropriate to take precautions to prevent it from taking place. Consequently, it is necessary to have good scientific knowledge (empirically supported) to adequately understand the extent of the problem and improve the way waste is being disposed of

Intelligent negotiation behaviour model for an open railway access market

In an open railway access market, the provisions of railway infrastructures and train services are separated and independent. Negotiations between the track owner and train service providers are thus required for the allocation of the track capacity and the formulation of the services timetables, in which each party, i.e. a stakeholder, exhibits intelligence from the previous negotiation experience to obtain the favourable terms and conditions for the track access. In order to analyse the realistic interacting behaviour among the stakeholders in the open railway access market schedule negotiations, intelligent learning capability should be included in the behaviour modelling. This paper presents a reinforcement learning approach on modelling the intelligent negotiation behaviour. The effectiveness of incorporating learning capability in the stakeholder negotiation behaviour is then demonstrated through simulation.

A two-Dimensional finite volume method for variable density flow and solute transport through saturated-unsaturated media

Extensive groundwater withdrawal has resulted in a severe seawater intrusion problem in the Gooburrum aquifers at Bundaberg, Queensland, Australia. Better management strategies can be implemented by understanding the seawater intrusion processes in those aquifers. To study the seawater intrusion process in the region, a two-dimensional density-dependent, saturated and unsaturated flow and transport computational model is used. The model consists of a coupled system of two non-linear partial differential equations. The first equation describes the flow of a variable-density fluid, and the second equation describes the transport of dissolved salt. A two-dimensional control volume finite element model is developed for simulating the seawater intrusion into the heterogeneous aquifer system at Gooburrum. The simulation results provide a realistic mechanism by which to study the convoluted transport phenomena evolving in this complex heterogeneous coastal aquifer.