489 resultados para Synthetic Traffic Generation

em Queensland University of Technology - ePrints Archive


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An intrinsic challenge associated with evaluating proposed techniques for detecting Distributed Denial-of-Service (DDoS) attacks and distinguishing them from Flash Events (FEs) is the extreme scarcity of publicly available real-word traffic traces. Those available are either heavily anonymised or too old to accurately reflect the current trends in DDoS attacks and FEs. This paper proposes a traffic generation and testbed framework for synthetically generating different types of realistic DDoS attacks, FEs and other benign traffic traces, and monitoring their effects on the target. Using only modest hardware resources, the proposed framework, consisting of a customised software traffic generator, ‘Botloader’, is capable of generating a configurable mix of two-way traffic, for emulating either large-scale DDoS attacks, FEs or benign traffic traces that are experimentally reproducible. Botloader uses IP-aliasing, a well-known technique available on most computing platforms, to create thousands of interactive UDP/TCP endpoints on a single computer, each bound to a unique IP-address, to emulate large numbers of simultaneous attackers or benign clients.

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This work-in-progress paper presents an ensemble-based model for detecting and mitigating Distributed Denial-of-Service (DDoS) attacks, and its partial implementation. The model utilises network traffic analysis and MIB (Management Information Base) server load analysis features for detecting a wide range of network and application layer DDoS attacks and distinguishing them from Flash Events. The proposed model will be evaluated against realistic synthetic network traffic generated using a software-based traffic generator that we have developed as part of this research. In this paper, we summarise our previous work, highlight the current work being undertaken along with preliminary results obtained and outline the future directions of our work.

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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.

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This research discusses some of the issues encountered while developing a set of WGEN parameters for Chile and advice for others interested in developing WGEN parameters for arid climates. The WGEN program is a commonly used and a valuable research tool; however, it has specific limitations in arid climates that need careful consideration. These limitations are analysed in the context of generating a set of WGEN parameters for Chile. Fourteen to 26 years of precipitation data are used to calculate precipitation parameters for 18 locations in Chile, and 3–8 years of temperature and solar radiation data are analysed to generate parameters for seven of these locations. Results indicate that weather generation parameters in arid regions are sensitive to erroneous or missing precipitation data. Research shows that the WGEN-estimated gamma distribution shape parameter (α) for daily precipitation in arid zones will tend to cluster around discrete values of 0 or 1, masking the high sensitivity of these parameters to additional data. Rather than focus on the length in years when assessing the adequacy of a data record for estimation of precipitation parameters, researchers should focus on the number of wet days in dry months in a data set. Analysis of the WGEN routines for the estimation of temperature and solar radiation parameters indicates that errors can occur when individual ‘months’ have fewer than two wet days in the data set. Recommendations are provided to improve methods for estimation of WGEN parameters in arid climates.

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Popular wireless network standards, such as IEEE 802.11/15/16, are increasingly adopted in real-time control systems. However, they are not designed for real-time applications. Therefore, the performance of such wireless networks needs to be carefully evaluated before the systems are implemented and deployed. While efforts have been made to model general wireless networks with completely random traffic generation, there is a lack of theoretical investigations into the modelling of wireless networks with periodic real-time traffic. Considering the widely used IEEE 802.11 standard, with the focus on its distributed coordination function (DCF), for soft-real-time control applications, this paper develops an analytical Markov model to quantitatively evaluate the network quality-of-service (QoS) performance in periodic real-time traffic environments. Performance indices to be evaluated include throughput capacity, transmission delay and packet loss ratio, which are crucial for real-time QoS guarantee in real-time control applications. They are derived under the critical real-time traffic condition, which is formally defined in this paper to characterize the marginal satisfaction of real-time performance constraints.

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Sustainable transport has become a necessity instead of an option, to address the problems of congestion and urban sprawl, whose effects include increased trip lengths and travel time. A more sustainable form of development, known as Transit Oriented Development (TOD) is presumed to offer sustainable travel choices with reduced need to travel to access daily destinations, by providing a mixture of land uses together with good quality of public transport service, infrastructure for walking and cycling. However, performance assessment of these developments with respect to travel characteristics of their inhabitants is required. This research proposes a five step methodology for evaluating the transport impacts of TODs. The steps for TOD evaluation include pre–TOD assessment, traffic and travel data collection, determination of traffic impacts, determination of travel impacts, and drawing outcomes. Typically, TODs are comprised of various land uses; hence have various types of users. Assessment of characteristics of all user groups is essential for obtaining an accurate picture of transport impacts. A case study TOD, Kelvin Grove Urban Village (KGUV), located 2km of north west of the Brisbane central business district in Australia was selected for implementing the proposed methodology and to evaluate the transport impacts of a TOD from an Australian perspective. The outcomes of this analysis indicated that KGUV generated 27 to 48 percent less traffic compared to standard published rates specified for homogeneous uses. Further, all user groups of KGUV used more sustainable modes of transport compared to regional and similarly located suburban users, with higher trip length for shopping and education trips. Although the results from this case study development support the transport claims of reduced traffic generation and sustainable travel choices by way of TODs, further investigation is required, considering different styles, scales and locations of TODs. The proposed methodology may be further refined by using results from new TODs and a framework for TOD evaluation may be developed.

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INTRODUCTION: Currently available volar locking plates for the treatment of distal radius fractures incorporate at least two distal screw rows for fixation of the metaphyseal fragment and have a variable-angle locking mechanism which allows placement of the screws in various directions There is, however no evidence that these plates translate into better outcomes or have superior biomechanical properties to first generation plates, which had a single distal screw row and fixed-angle locking. The aim of our biomechanical study was to compare fixed-angle single-row plates with variable-angle multi-row plates to clarify the optimal number of locking screws. MATERIALS AND METHODS: Five different plate-screw combinations of three different manufacturers were tested, each group consisting of five synthetic fourth generation distal radius bones. An AO type C2 fracture was created and the fractures were plated according to each manufacturer's recommendations. The specimens then underwent cyclic and load-to-failure testing. An optical motion analysis system was used to detect displacement of fragments. RESULTS: No significant differences were detected after cyclic loading as well as after load-to-failure testing, neither in regard to axial deformation, implant rigidity or maximum displacement. The fixed-angle single-row plate showed the highest pre-test rigidity, least increase in post-testing rigidity and highest load-to-failure rigidity and least radial shortening. The radial shortening of plates with two distal screw rows was 3.1 and 4.3 times higher, respectively, than that of the fixed-angle single-row plate. CONCLUSION: The results of our study indicate that two distal screw rows do not add to construct rigidity and resistance against loss of reduction. Well conducted clinical studies based on the findings of biomechanical studies are necessary to determine the optimal number of screws necessary to achieve reproducibly good results in the treatment of distal radius fractures.

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This paper presents a Genetic Algorithms (GA) approach to resolve traffic conflicts at a railway junction. The formulation of the problem for the suitable application of GA will be discussed and three neighborhoods have been proposed for generation evolution. The performance of the GA is evaluated by computer simulation. This study paves the way for more applications of artificial intelligence techniques on a rather conservative industry.

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Findings from an online survey conducted by Queensland University of Technology (QUT) shows that Australia is suffering from a lack of data reflecting trip generation for use in Traffic Impact Assessments (TIAs). Current independent variables for trip generation estimation are not able to create robust outcomes as well. It is also challenging to account for the impact of the new development on public and active transport as well as the effect of trip chaining behaviour in Australian TIA studies. With this background in mind, research is being implemented by QUT to find a new approach developing a combined model of trip generation and mode choice with consideration of trip chaining effects. It is expected that the model will provide transferable outcomes as it is developed based on socio-demographic parameters. Child Care Centres within the Brisbane area have been nominated for model development. At the time, the project is in the data collection phase. Findings from the pilot survey associated with capturing trip chaining and mode choice information reveal that applying questionnaire is able to capture required information in an acceptable level. The result also reveals that several centres within an area should be surveyed in order to provide sufficient data for trip chaining and modal split analysis.

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The deployment of new emerging technologies, such as cooperative systems, allows the traffic community to foresee relevant improvements in terms of traffic safety and efficiency. Autonomous vehicles are able to share information about the local traffic state in real time, which could result in a better reaction to the mechanism of traffic jam formation. An upstream single-hop radio broadcast network can improve the perception of each cooperative driver within a specific radio range and hence the traffic stability. The impact of vehicle to vehicle cooperation on the onset of traffic congestion is investigated analytically and through simulation. A next generation simulation field dataset is used to calibrate the full velocity difference car-following model, and the MOBIL lane-changing model is implemented. The robustness of the calibration as well as the heterogeneity of the drivers is discussed. Assuming that congestion can be triggered either by the heterogeneity of drivers' behaviours or abnormal lane-changing behaviours, the calibrated car-following model is used to assess the impact of a microscopic cooperative law on egoistic lane-changing behaviours. The cooperative law can help reduce and delay traffic congestion and can have a positive effect on safety indicators.

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Studying the rate of cell migration provides insight into fundamental cell biology as well as a tool to assess the functionality of synthetic surfaces and soluble environments used in tissue engineering. The traditional tools used to study cell migration include the fence and wound healing assays. In this paper we describe the development of a microchannel based device for the study of cell migration on defined surfaces. We demonstrate that this device provides a superior tool, relative to the previously mentioned assays, for assessing the propagation rate of cell wave fronts. The significant advantage provided by this technology is the ability to maintain a virgin surface prior to the commencement of the cell migration assay. Here, the device is used to assess rates of mouse fibroblasts (NIH 3T3) and human osteosarcoma (SaOS2) cell migration on surfaces functionalized with various extracellular matrix proteins as a demonstration that confining cell migration within a microchannel produces consistent and robust data. The device design enables rapid and simplistic assessment of multiple repeats on a single chip, where surfaces have not been previously exposed to cells or cellular secretions.

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This paper studies traffic hysteresis arising in traffic oscillations from a behavioral perspective. It is found that the occurrence and type of traffic hysteresis is closely correlated with driver behavior when experiencing traffic oscillations and with the time driver reaction begins relative to the starting deceleration wave. Statistical results suggest that driver behavior is different depending on its position along the oscillation. This suggests that different car-following models should be used inside the different stages of an oscillation in order to replicate realistic congestion features.

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An online survey was conducted to investigate the views and experiences of Australian traffic and transport professionals about practical problems and issues in terms of trip generation and trip chaining for use in Transport Impact Assessment (TIA). Findings from this survey revealed that there is a shortage of appropriate data related to trip generation estimation for use in TIAs in Australia. Establishing a National Trip Generation Database (NTGD) with a centralised responsible organisation for collecting and publishing trip generation data based on federal and state governments’ contribution was found the most accepted solution for resolving this shortage as well as providing national standards and guidelines associated with trip generation definitions, data collection methodology, and TIA preparation process based on updated research. Finally, the study recognised the importance of the trip chaining effects on trip generation estimation and identified most prevalent land uses subject to trip chaining in terms of TIA.

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Synthetic hydrogels selectively decorated with cell adhesion motifs are rapidly emerging as promising substrates for 3D cell culture. When cells are grown in 3D they experience potentially more physiologically relevant cell-cell interactions and physical cues compared with traditional 2D cell culture on stiff surfaces. A newly developed polymer based on poly(2-oxazoline)s has been used for the first time to control attachment of fibroblast cells and is discussed here for its potential use in 3D cell culture with particular focus on cancer cells towards the ultimate aim of high throughput screening of anti-cancer therapies. Advantages and limitations of using poly(2-oxazoline) hydrogels are discussed and compared with more established polymers, especially polyethylene glycol (PEG).

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Next Generation Sequencing (NGS) has revolutionised molecular biology, resulting in an explosion of data sets and an increasing role in clinical practice. Such applications necessarily require rapid identification of the organism as a prelude to annotation and further analysis. NGS data consist of a substantial number of short sequence reads, given context through downstream assembly and annotation, a process requiring reads consistent with the assumed species or species group. Highly accurate results have been obtained for restricted sets using SVM classifiers, but such methods are difficult to parallelise and success depends on careful attention to feature selection. This work examines the problem at very large scale, using a mix of synthetic and real data with a view to determining the overall structure of the problem and the effectiveness of parallel ensembles of simpler classifiers (principally random forests) in addressing the challenges of large scale genomics.