Centre for Research in Distributed Technologies (CREDIT)
CREDIT research is focused on three areas: Secure Services, Communications and Networks and Distributed Processing.
Recent Submissions
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Web browser artefacts in private and portable modes: a forensic investigationWeb browsers are essential tools for accessing the internet. Extra complexities are added to forensic investigations when recovering browsing artefacts as portable and private browsing are now common and available in popular web browsers. Browsers claim that whilst operating in private mode, no data is stored on the system. This paper investigates whether the claims of web browsers discretion are true by analysing the remnants of browsing left by the latest versions of Internet Explorer, Chrome, Firefox, and Opera when used in a private browsing session, as a portable browser, and when the former is running in private mode. Some of our key findings show how forensic analysis of the file system recovers evidence from IE while running in private mode whereas other browsers seem to maintain better user privacy. We analyse volatile memory and demonstrate how physical memory by means of dump files, hibernate and page files are the key areas where evidence from all browsers will still be recoverable despite their mode or location they run from.
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Anonymity networks and the fragile cyber ecosystemIt is well known that government agencies have had the capability to eavesdrop on public switched telephone networks for many decades.1 However, with the growing use of the Internet and the increasing technical capabilities of agencies to conduct mass surveillance, an individual's right to privacy is of far greater concern in recent years. The ethical issues surrounding privacy, anonymity and mass-surveillance are complicated, with compelling arguments for and against, due in part to the fact that privacy and anonymity are desired by criminals and terrorists, not just individuals who care about their privacy.
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CCBS – a method to maintain memorability, accuracy of password submission and the effective password space in click-based visual passwordsText passwords are vulnerable to many security attacks due to a number of reasons such as the insecure practices of end users who select weak passwords to maintain their long term memory. As such, visual password (VP) solutions were developed to maintain the security and usability of user authentication in collaborative systems. This paper focuses on the challenges facing click-based visual password systems and proposes a novel method in response to them. For instance, Hotspots reveal a serious vulnerability. They occur because users are attracted to specific parts of an image and neglect other areas. Undertaking image analysis to identify these high probability areas can assist dictionary attacks. Another concern is that click-based systems do not guide users towards the correct click-point they are aiming to select. For instance, users might recall the correct spot or area but still fail to include their click within the tolerance distance around the original click-point which results in more incorrect password submissions. Nevertheless, the Passpoints study by Wiedenbeck et al., 2005 inspected the retention of their VP in comparison with text passwords over the long term. Despite being cued-recall the successful rate of their VP submission was not superior to text passwords as it decreased from 85% (the instant retention on the day of registration) to 55% after 2 weeks. This result was identical to that of the text password in the same experiment. The successful submission rates after 6 weeks were also 55% for both VP and text passwords. This paper addresses these issues, and then presents a novel method (CCBS) as a usable solution supported by an empirical proof. A user study is conducted and the results are evaluated against a comparative study.
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Responsibility and non-repudiation in resource-constrained Internet of Things scenariosThe proliferation and popularity of smart autonomous systems necessitates the development of methods and models for ensuring the effective identification of their owners and controllers. The aim of this paper is to critically discuss the responsibility of Things and their impact on human affairs. This starts with an in-depth analysis of IoT Characteristics such as Autonomy, Ubiquity and Pervasiveness. We argue that Things governed by a controller should have an identifiable relationship between the two parties and that authentication and non-repudiation are essential characteristics in all IoT scenarios which require trustworthy communications. However, resources can be a problem, for instance, many Things are designed to perform in low-powered hardware. Hence, we also propose a protocol to demonstrate how we can achieve the authenticity of participating Things in a connectionless and resource-constrained environment.
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How technology can mitigate and counteract cyber-stalking and online groomingWith the virtual world becoming part of the social lives of adults and minors alike, new attack vectors emerged to increase the severity of human-related attacks to a level the community have not experience before. This article investigates and shares an outline on how technology could emerge further to counteract and mitigate the damage caused by online perpetrators. The review encourages approaching online harassment, stalking, bullying, grooming and their likes with an Incident Response methodology in mind. This includes a detection phase utilising automated methods to identify and classify such attacks, conduct digital forensic investigations to analyse the nature of the offence and reserve evidence, taking preventive measures as part of the reaction towards the problem such as filtering unwanted communications and finally looking at how we can rely on applicable computing to support and educate the victims.
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User-oriented ontology-based clustering of stored memoriesThis research addresses the needs of people who find reminiscence helpful. It focuses on the development of a computerised system called a Life Story Book (LSB), which facilitates access and retrieval of stored memories used as the basis for positive interactions between elderly and young, and especially between people with cognitive impairment and members of their family or caregivers. To facilitate information management and dynamic generation of content, this paper introduces a semantic model of LSB which is based on the use of ontologies and advanced algorithms for feature selection and dimension reduction. Furthermore, the paper defines a light weight user-oriented domain ontology and its building principles. It then proposes an algorithm called Onto-SVD, which uses the user-oriented ontology to automatically detect the semantic relations within the stored memories. It combines semantic feature selection with k-means clustering and Singular Value Decomposition (SVD) to achieve topic identification based on semantic similarity. The experiments conducted explore the effect of semantic feature selection as a result of establishing indirect relations, with the help of the ontology, within the information content. The results show that Onto-SVD considerably outperforms SVD in both topic identification and semantic disambiguation.
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User-centered design of a dynamic-autonomy remote interaction concept for manipulation-capable robots to assist elderly people in the homeIn this article, we describe the development of a human-robot interaction concept for service robots to assist elderly people in the home with physical tasks. Our approach is based on the insight that robots are not yet able to handle all tasks autonomously with sufficient reliability in the complex and heterogeneous environments of private homes. We therefore employ remote human operators to assist on tasks a robot cannot handle completely autonomously. Our development methodology was user-centric and iterative, with six user studies carried out at various stages involving a total of 241 participants. The concept is under implementation on the Care-O-bot 3 robotic platform. The main contributions of this article are (1) the results of a survey in form of a ranking of the demands of elderly people and informal caregivers for a range of 25 robot services, (2) the results of an ethnography investigating the suitability of emergency teleassistance and telemedical centers for incorporating robotic teleassistance, and (3) a user-validated human-robot interaction concept with three user roles and corresponding three user interfaces designed as a solution to the problem of engineering reliable service robots for home environments.
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Toward behavioral web services using policiesMaking Web services context-aware is a challenge. This is like making Web service expose appropriate behaviors in response to changes detected in the environment. Context awareness requires a review and extension of the current execution model of Web services. This paper discusses the seamless combination of context and policy to manage behaviors that Web services expose during composition and in response to changes in the environment. For this purpose, a four-layer approach is devised. These layers are denoted by policy, user, Web service, and resource. In this approach, behavior management and binding are subject to executing policies of types permission, obligation, restriction, and dispensation. A prototype that illustrates how context and policy are woven into Web services composition scenarios is presented as well.
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SpiNNaker: a 1-W 18-core system-on-chip for massively-parallel neural network simulationThe modelling of large systems of spiking neurons is computationally very demanding in terms of processing power and communication. SpiNNaker - Spiking Neural Network architecture - is a massively parallel computer system designed to provide a cost-effective and flexible simulator for neuroscience experiments. It can model up to a billion neurons and a trillion synapses in biological real time. The basic building block is the SpiNNaker Chip Multiprocessor (CMP), which is a custom-designed globally asynchronous locally synchronous (GALS) system with 18 ARM968 processor nodes residing in synchronous islands, surrounded by a lightweight, packet-switched asynchronous communications infrastructure. In this paper, we review the design requirements for its very demanding target application, the SpiNNaker micro-architecture and its implementation issues. We also evaluate the SpiNNaker CMP, which contains 100 million transistors in a 102-mm2 die, provides a peak performance of 3.96 GIPS, and has a peak power consumption of 1 W when all processor cores operate at the nominal frequency of 180 MHz. SpiNNaker chips are fully operational and meet their power and performance requirements.
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On distributed and coordinated resource allocation for interference mitigation in self-organizing LTE networksWe propose a distributed and coordinated radio resource allocation algorithm for orthogonal frequency division multiple access (OFDMA)-based cellular networks to self-organize efficient and stable frequency reuse patterns. In the proposed radio resource allocation algorithm, each cell independently and dynamically allocates modulation and coding scheme (MCS), resource block (RB), and transmit power to its users in a way that its total downlink (DL) transmit power is minimized, while users' throughput demands are satisfied. Moreover, each cell informs neighboring cells of the RBs that have been scheduled for its cell-edge users' DL transmissions through message passing. Accordingly, the neighboring cells abstain from assigning high transmit powers to the specified RBs. Extensive simulation results attempt to demonstrate that DL power control on a per-RB basis may play a key role in future networks, and show that the distributed minimization of DL transmit power at each cell, supported by intercell interference coordination, is able to provide a 20% improvement of network throughput, considerably reduce the number of user outages, and significantly enhance spatial reuse, as compared to cutting-edge resource allocation schemes.
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General results on SNR statistics involving EESM-based frequency selective feedbacksNovel methods of obtaining the moment generating function (MGF) and moments of the exponential effective SNR mapping (EESM) signal-to-noise ratio (SNR) over N jointly distributed fading channels are presented. Based on these methods, novel explicit expressions of the MGF and moments over arbitrary number of correlated Nakagami-m fading channels are proposed. Numerical evaluation of these expressions shows that the proposed approach can be a useful and efficient analytical tool in characterizing the statistics of EESM over correlated Nakagami-m fading channels.
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Geometric polarimetry—part I: spinors and wave statesA new formal approach for the representation of polarization states of coherent and partially coherent electromagnetic plane waves is presented. Its basis is a purely geometric construction for the normalized complex-analytic coherent wave as a generating line in the sphere of wave directions and whose Stokes vector is determined by the intersection with the conjugate generating line. The Poincaré sphere is now located in physical space, simply a coordination of the wave sphere, with its axis aligned with the wave vector. Algebraically, the generators representing coherent states are represented by spinors, and this is made consistent with the spinor-tensor representation of electromagnetic theory by means of an explicit reference spinor that we call the phase flag. As a faithful unified geometric representation, the new model provides improved formal tools for resolving many of the geometric difficulties and ambiguities that arise in the traditional formalism.
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Depth mapping of integral images through viewpoint image extraction with a hybrid disparity analysis algorithmIntegral imaging is a technique capable of displaying 3–D images with continuous parallax in full natural color. It is one of the most promising methods for producing smooth 3–D images. Extracting depth information from integral image has various applications ranging from remote inspection, robotic vision, medical imaging, virtual reality, to content-based image coding and manipulation for integral imaging based 3–D TV. This paper presents a method of generating a depth map from unidirectional integral images through viewpoint image extraction and using a hybrid disparity analysis algorithm combining multi-baseline, neighborhood constraint and relaxation strategies. It is shown that a depth map having few areas of uncertainty can be obtained from both computer and photographically generated integral images using this approach. The acceptable depth maps can be achieved from photographic captured integral images containing complicated object scene.
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Compression of 3D integral images using 3D wavelet transformIntegral imaging is a technique capable of displaying 3D images with continuous parallax in full natural color. It has been reported by many research groups and is becoming a viable alternative for 3D television. With the development of 3D integral imaging, image compression becomes mandatory for the storage and transmission of 3D integral images. In this paper, the use of the lifting scheme in the application of a 3D Wavelet Transform for the compression of 3D Integral Images is proposed. The method requires the extraction of different viewpoint images from an integral image. The 3D wavelet decomposition is computed by applying three separate 1D transforms along the coordinate axes of the given sequence of Viewpoint Images. The spatial wavelet decompositions on a single viewpoint and on the inter-viewpoint images are performed using the biorthogonal Cohen-Debauchies-Feauveau 9/7 and 5/3 filter banks, respectively. All the resulting wavelet coefficients from application of the 3D wavelet decomposition are arithmetic encoded. Simulations are performed on a set of different grey level 3D Integral Images using a uniform scalar quantizer with deadzone. The results for the average of the four intensity distributions are presented and compared with previous use of 2D DWT and 3D-DCT based schemes. It was found that the algorithm achieves better rate-distortion performance and reconstructs the images with much better image quality at very low bit rates.
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Characterization of the numerical Group velocity in Yee's FDTD GridA method is introduced for the optimization of the numerical group velocity in standard finite-difference time-domain (FDTD) electromagnetic simulations. Through this method analytical expressions for the extrema of are presented for the first time, thus also characterizing its anisotropy. The knowledge of these expressions is hence essential for the evaluation of the anisotropy error in FDTD-based electrodynamics simulations of the propagation of wavepackets in 2D and 3D. This can be of assistance, for example, in the design of error-bounded FDTD simulations with pulsed sources at low computational cost.
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autopin – Automated Optimization of Thread-to-Core Pinning on Multicore SystemsIn this paper we present a framework for automatic detection and application of the best binding between threads of a running parallel application and processor cores in a shared memory system, by making use of hardware performance counters. This is especially important within the scope of multicore architectures with shared cache levels. We demonstrate that many applications from the SPEC OMP benchmark show quite sensitive runtime behavior depending on the thread/core binding used. In our tests, the proposed framework is able to find the best binding in nearly all cases. The proposed framework is intended to supplement job scheduling systems for better automatic exploitation of systems with multicore processors, as well as making programmers aware of this issue by providing measurement logs.
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An interference-aware virtual clustering paradigm for resource management in cognitive femtocell networksFemtocells represent a promising alternative solution for high quality wireless access in indoor scenarios where conventional cellular system coverage can be poor. They are randomly deployed by the end user, so only post-deployment network planning is possible. Furthermore, this uncoordinated deployment creates severe interference to co-located femtocells, especially in dense deployments. This paper presents a new architecture using a generalised virtual cluster femtocell (GVCF) paradigm, which groups together FAP into logical clusters. It guarantees severely interfering and overlapping femtocells are assigned to different clusters. Since each cluster operates on different band of frequencies, the corresponding virtual cluster controller only has to manage its own FAPs, so the overall system complexity is low. The performance of the GVCF algorithm is analysed from both a resource availability and cluster number perspective. Simulation results conclusively corroborate the superior performance of the GVCF model in interference mitigation, particularly in high density FAP scenarios.
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Adaptive bees algorithm : bioinspiration from honeybee foraging to optimize fuel economy of a semi-track air-cushion vehicleThis interdisciplinary study covers bionics, optimization and vehicle engineering. Semi-track air-cushion vehicle (STACV) provides a solution to transportation on soft terrain, whereas it also brings a new problem of excessive fuel consumption. By mimicking the foraging behaviour of honeybees, the bioinspired adaptive bees algorithm (ABA) is proposed to calculate its running parameters for fuel economy optimization. Inherited from the basic algorithm prototype, it involves parallel-operated global search and local search, which undertake exploration and exploitation, respectively. The innovation of this improved algorithm lies in the adaptive adjustment mechanism of the range of local search (called ‘patch size’) according to the source and the rate of change of the current optimum. Three gradually in-depth experiments are implemented for 143 kinds of soils. First, the two optimal STACV running parameters present the same increasing or decreasing trend with soil parameters. This result is consistent with the terramechanics-based theoretical analysis. Second, the comparisons with four alternative algorithms exhibit the ABA's effectiveness and efficiency, and accordingly highlight the advantage of the novel adaptive patch size adjustment mechanism. Third, the impacts of two selected optimizer parameters to optimization accuracy and efficiency are investigated and their recommended values are thus proposed.
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Integrating robot task planner with common-sense knowledge base to improve the efficiency of planningThis paper presents a developed approach for intelligently generating symbolic plans by mobile robots acting in domestic environments, such as offices and houses. The significance of the approach lies in developing a new framework that consists of the new modeling of high-level robot actions and then their integration with common-sense knowledge in order to support a robotic task planner. This framework will enable interactions between the task planner and the semantic knowledge base directly. By using common-sense domain knowledge, the task planner will take into consideration the properties and relations of objects and places in its environment, before creating semantically related actions that will represent a plan. This plan will accomplish the user order. The robot task planner will use the available domain knowledge to check the next related actions to the current one and the action's conditions met will be chosen. Then the robot will use the immediately available knowledge information to check whether the plan outcomes are met or violated.
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Magnetic surface patterns made by non-destructive laser interferenceThis paper presents a method to make magnetic surface patterns by non-destructive laser interference, and periodic magnetic fringes produced on magnetic material surfaces are investigated by magnetic force microscopy (MFM). Various thermal effects are obtained by two beam laser interference with different exposure times and pulse energies. The experimental results have shown that magnetic patterns can be made on magnetic materials by laser interference without any damage to the surfaces. The method provides a way for the rapid producing of magnetic marks or recording magnetic data in a large area on a magnetic material surface, and it could be useful for biological, material, optical, electronic and information engineering applications.