Portrait of Professor Gareth Howells

Professor Gareth Howells

Professor of Secure Electronic Systems

About

Gareth Howells has been involved in research relating to security, biometrics and pattern classification techniques for over twenty five years and he has been awarded, either individually or jointly, several major research grants relating to the pattern classification and security fields, publishing over 180 papers in the technical literature. Recent work has been directed towards the development of secure device authentication systems with a focus on Internet of Things (IoT) which has received significant funding from the a variety of sources.

Research interests


Publications

Showing 50 of 197 total publications in the Kent Academic Repository. View all publications.

Article

  • Gillham, M. et al. (2017). Feature determination from powered wheelchair user joystick input characteristics for adapting driving assistance. Wellcome Open Research [Online] 2:93. Available at: https://doi.org/10.12688/wellcomeopenres.12280.2.
    Background: Many powered wheelchair users find their medical condition and
    their ability to drive the wheelchair will change over time. In order to maintain
    their independent mobility, the powered chair will require adjustment over time
    to suit the user's needs, thus regular input from healthcare professionals is
    required. These limited resources can result in the user having to wait weeks
    for appointments, resulting in the user losing independent mobility,
    consequently affecting their quality of life and that of their family and carers. In
    order to provide an adaptive assistive driving system, a range of features need
    to be identified which are suitable for initial system setup and can automatically
    provide data for re-calibration over the long term.
    Methods: A questionnaire was designed to collect information from powered
    wheelchair users with regard to their symptoms and how they changed over
    time. Another group of volunteer participants were asked to drive a test platform
    and complete a course which represented manoeuvring in a very confined
    space as quickly as possible. Two of those participants were also monitored
    over a longer period in their normal home daily environment. Features, thought
    to be suitable, were examined using pattern recognition classifiers to determine
    their suitability for identifying the changing user input over time.
    Results: The results are not designed to provide absolute insight into the
    individual user behaviour, as no ground truth of their ability has been
    determined, they do nevertheless demonstrate the utility of the measured
    features to provide evidence of the users’ changing ability over time whilst
    driving a powered wheelchair.
    Conclusions: Determining the driving features and adjustable elements
    provides the initial step towards developing an adaptable assistive technology
    for the user when the ground truths of the individual and their machine have
    been learned by a smart pattern recognition system
  • Gillham, M. et al. (2017). Stakeholder views addressing the development and uptake of powered wheelchair assistive technology. Disability and Rehabilitation: Assistive Technology [Online]. Available at: http://dx.doi.org/10.1080/17483107.2017.1416186.
    Purpose: The objective of this research is to identify stakeholder views with regard to the development of effective powered wheelchair assistive technologies more suited to the user and carer needs, whilst also meeting the requirements for other stakeholders, such that developers can be better guided towards producing solutions which have a better chance of getting to the market place and hence to the end user.
    Method: A questionnaire was designed to collect the views of all stakeholders and circulated to a statistically representative number of them. The question rating data was then checked for correlation between groups, and within groups, to establish validity.
    Results: The 74 stakeholders across the eight classes who responded had a good correlation between each other, with a cross class ‘Pearson’s correlation’ ranging between 0.7 and 0.95, and the ‘Fleiss’s Kappa reliability of agreement’ within each class ranging between 0.07 and 0.36.
    Conclusions: This research has identified that all stakeholders should be involved in the development of the technology and that some may benefit in ‘role-reversal’ to help understand user problems and stakeholder concerns more clearly. Cost was a significant barrier to the uptake of appropriate technology, and training of users and carers was a major issue. Furthermore development should not increase user isolation and the impact on the user must be monitored for ‘quality of life’. Technical support and training should be given to the user and their carers and equipment must be adaptive to meet the changing needs of the user.
  • Hu, Y., Sirlantzis, K. and Howells, G. (2016). A novel iris weight map method for less constrained iris recognition based on bit stability and discriminability. Image and Vision Computing [Online] 58:168-180. Available at: http://dx.doi.org/10.1016/j.imavis.2016.05.003.
    In this paper, we propose and investigate a novel iris weight map method for iris matching stage to improve less constrained iris recognition. The proposed iris weight map considers both intra-class bit stability and inter-class bit discriminability of iris codes. We model the intra-class bit stability in a stability map to improve the intra-class matching. The stability map assigns more weight to the bits that have values more consistent with their noiseless and stable estimates obtained using a low rank approximation from a set of noisy training images. Also, we express the inter-class bit discriminability in a discriminability map to enhance the inter-class separation. We calculate the discriminability map using a 1-to-N strategy, emphasizing the bits with more discriminative power in iris codes. The final iris weight map is the combination of the stability map and the discriminability map. We conduct experimental analysis on four publicly available datasets captured in varying less constrained conditions. The experimental results demonstrate that the proposed iris weight map achieves generally improved identification and verification performance compared to state-of-the-art methods.
  • Hu, Y., Sirlantzis, K. and Howells, G. (2016). Optimal Generation of Iris Codes for Iris Recognition. IEEE Transactions on Information Forensics and Security [Online]. Available at: http://doi.org/10.1109/TIFS.2016.2606083.
    The calculation of binary iris codes from feature values (e.g. the result of Gabor transform) is a key step in iris recognition systems. Traditional binarization method based on the sign of feature values has achieved very promising performance. However, currently, little research focuses on a deeper insight into this binarization method to produce iris codes. In this paper, we illustrate the iris code calculation from the perspective of optimization. We demonstrate that the traditional iris code is the solution of an optimization problem which minimizes the distance between the feature values and iris codes. Furthermore, we show that more effective iris codes can be obtained by adding terms to the objective function of this optimization problem. We investigate two additional objective terms. The first objective term exploits the spatial relationships of the bits in different positions of an iris code. The second objective term mitigates the influence of less reliable bits in iris codes. The two objective terms can be applied to the optimization problem individually, or in a combined scheme. We conduct experiments on four benchmark datasets with varying image quality. The experimental results demonstrate that the iris code produced by solving the optimization problem with the two additional objective terms achieves a generally improved performance in comparison to the traditional iris code calculated by binarizing feature values based on their signs.
  • Hu, Y. et al. (2016). An online background subtraction algorithm deployed on a NAO humanoid robot based monitoring system. Robotics and Autonomous Systems [Online] 85:37-47. Available at: http://dx.doi.org/10.1016/j.robot.2016.08.013.
    In this paper, we design a fast background subtraction algorithm and deploy this algorithm on a monitoring system
    based on NAO humanoid robot. The proposed algorithm detects a contiguous foreground via a contiguously weighted
    linear regression (CWLR) model. It consists of a background model and a foreground model. The background model
    is a regression based low rank model. It seeks a low rank background subspace and represents the background as the
    linear combination of the basis spanning the subspace. The foreground model promotes the contiguity in the foreground
    detection. It encourages the foreground to be detected as whole regions rather than separated pixels. We formulate
    the background and foreground model into a contiguously weighted linear regression problem. This problem can be
    solved efficiently via an alternating optimization approach which includes continuous and discrete variables. Given an
    image sequence, we use the first few frames to incrementally initialize the background subspace, and we determine
    the background and foreground in the following frames in an online scheme using the proposed CWLR model, with
    the background subspace continuously updated using the detected background information. The proposed algorithm is
    implemented by Python on a NAO humanoid robot based monitoring system. This system consists of a control station
    and a Nao robot. The Nao robot acts as a mobile probe. It captures image sequence and sends it to the control station.
    The control station serves as a control terminal. It sends commands to control the behaviour of Nao robot, and it
    processes the image data sent by Nao. This system can be used for living environment monitoring and form the basis for
    many vision-based applications like fall detection and scene understanding. The experimental comparisons with most
    recent algorithms on both benchmark dataset and NAO captures demonstrate the high effectiveness of the proposed
    algorithm.
  • Hu, Y., Sirlantzis, K. and Howells, G. (2016). Signal-Level Information Fusion for Less Constrained Iris Recognition using Sparse-Error Low Rank Matrix Factorization. IEEE Transactions on Information Forensics and Security [Online]:1549-1564. Available at: http://dx.doi.org/10.1109/TIFS.2016.2541612.
    Iris recognition systems working in less constrained environments with the subject at-a-distance and on-the-move suffer from the noise and degradations in the iris captures. These noise and degradations significantly deteriorate iris recognition performance. In this paper, we propose a novel signal-level information fusion method to mitigate the influence of noise and degradations for less constrained iris recognition systems. The proposed method is based on low rank approximation (LRA). Given multiple noisy captures of the same eye, we assume that: 1) the potential noiseless images lie in a low rank subspace and 2) the noise is spatially sparse. Based on these assumptions, we seek an LRA of noisy captures to separate the noiseless images and noise for information fusion. Specifically, we propose a sparse-error low rank matrix factorization model to perform LRA, decomposing the noisy captures into a low rank component and a sparse error component. The low rank component estimates the potential noiseless images, while the error component models the noise. Then, the low rank and error components are utilized to perform signal-level fusion separately, producing two individually fused images. Finally, we combine the two fused images at the code level to produce one iris code as the final fusion result. Experiments on benchmark data sets demonstrate that the proposed signal-level fusion method is able to achieve a generally improved iris recognition performance in less constrained environment, in comparison with the existing iris recognition algorithms, especially for the iris captures with heavy noise and low quality.
  • Gillham, M. and Howells, G. (2015). A Dynamic Localized Adjustable Force Field Method for Real-time Assistive Non-holonomic Mobile Robotics. International Journal of Advanced Robotic Systems [Online]:1. Available at: http://doi.org/10.5772/61190.
    Providing an assistive navigation system that augments
    rather than usurps user control of a powered wheelchair
    represents a significant technical challenge. This paper
    evaluates an assistive collision avoidance method for a
    powered wheelchair that allows the user to navigate safely
    whilst maintaining their overall governance of the platform
    motion. The paper shows that by shaping, switching and
    adjusting localized potential fields we are able to negotiate
    different obstacles by generating a more intuitively natural
    trajectory, one that does not deviate significantly from the
    operator in the loop desired-trajectory. It can also be seen
    that this method does not suffer from the local minima
    problem, or narrow corridor and proximity oscillation,
    which are common problems that occur when using
    potential fields. Furthermore this localized method enables
    the robotic platform to pass very close to obstacles, such as
    when negotiating a narrow passage or doorway.
  • Zhai, X. et al. (2015). A Method for Detecting Abnormal Program Behavior on Embedded Devices. IEEE Transactions on Information Forensics and Security [Online] 10:1692-1704. Available at: http://doi.org/10.1109/TIFS.2015.2422674.
    A potential threat to embedded systems is the execution of unknown or malicious software capable of triggering harmful system behavior, aimed at theft of sensitive data or causing damage to the system. Commercial off-the-shelf embedded devices, such as embedded medical equipment, are more vulnerable as these type of products cannot be amended conventionally or have limited resources to implement protection mechanisms. In this paper, we present a self-organizing map (SOM)-based approach to enhance embedded system security by detecting abnormal program behavior. The proposed method extracts features derived from processor's program counter and cycles per instruction, and then utilises the features to identify abnormal behavior using the SOM. Results achieved in our experiment show that the proposed method can identify unknown program behaviors not included in the training set with over 98.4% accuracy.
  • Hu, Y., Sirlantzis, K. and Howells, G. (2015). Iris liveness detection using regional features. Pattern Recognition Letters [Online]. Available at: https://doi.org/10.1016/j.patrec.2015.10.010.
    In this paper, we exploit regional features for iris liveness detection. Regional features are designed based on the relationship of the features in neighbouring regions. They essentially capture the feature distribution among neighbouring regions. We construct the regional features via two models: spatial pyramid and relational measure which seek the feature distributions in regions with varying size and shape respectively. The spatial pyramid model extracts features from coarse to fine grid regions, and, it models a local to global feature distribution. The local distribution captures the local feature variations while the global distribution includes the information that is more robust to translational transform. The relational measure is based on a feature-level convolution operation defined in this paper. By varying the shape of the convolution kernel, we are able to obtain the feature distribution in regions with different shapes. To combine the feature distribution information in regions with varying size and shape, we fuse the results based on the two models at the score level. Experimental results on benchmark datasets demonstrate that the proposed method achieves an improved performance compared to state-of-the-art features.
  • Hu, Y., Sirlantzis, K. and Howells, G. (2015). Improving colour iris segmentation using a model selection technique. Pattern Recognition Letters [Online] 57:24-32. Available at: http://doi.org/10.1016/j.patrec.2014.12.012.
    In this paper, we propose a novel method to improve the reliability and accuracy of colour iris segmentation for captures both from static and mobile devices. Our method is a fusion strategy based on selection among the segmentation outcomes of different segmentation methods or models. First, we present and analyse an iris segmentation framework which uses three different models to show that improvements can be obtained by selection among the outcomes generated by the three models. Then, we introduce a model selection method which defines the optimal segmentation based on a ring-shaped region around the outer segmentation boundary identified by each model. We use the histogram of oriented gradients (HOG) as features extracted from the ring-shaped region, and train a SVM-based classifier which provides the selection decision. Experiments on colour iris datasets, captured by mobile devices and static camera, show that the proposed method achieves an improved performance compared to the individual iris segmentation models and existing algorithms.
  • Zhai, X. et al. (2015). Exploring ICMetrics to detect abnormal program behaviour on embedded devices. Journal of Systems Architecture [Online] 61:567-575. Available at: http://dx.doi.org/10.1016/j.sysarc.2015.07.007.
    Execution of unknown or malicious software on an embedded system may trigger harmful system behaviour targeted at stealing sensitive data and/or causing damage to the system. It is thus considered a potential and significant threat to the security of embedded systems. Generally, the resource constrained nature of commercial off-the-shelf (COTS) embedded devices, such as embedded medical equipment, does not allow computationally expensive protection solutions to be deployed on these devices, rendering them vulnerable. A Self-Organising Map (SOM) based and Fuzzy C-means based approaches are proposed in this paper for detecting abnormal program behaviour to boost embedded system security. The presented technique extracts features derived from processor’s Program Counter (PC) and Cycles per Instruction (CPI), and then utilises the features to identify abnormal behaviour using the SOM. Results achieved in our experiment show that the proposed SOM based and Fuzzy C-means based methods can identify unknown program behaviours not included in the training set with 90.9% and 98.7% accuracy.
  • Ye, B. et al. (2015). Multi-dimensional key generation of ICMetrics for cloud computing. Journal of Cloud Computing [Online] 4. Available at: http://doi.org/10.1186/s13677-015-0044-6.
    Despite the rapid expansion and uptake of cloud based services, lack of trust in the provenance of such services represents a significant inhibiting factor in the further expansion of such service. This paper explores an approach to assure trust and provenance in cloud based services via the generation of digital signatures using properties or features derived from their own construction and software behaviour. The resulting system removes the need for a server to store a private key in a typical Public/Private-Key Infrastructure for data sources. Rather, keys are generated at run-time by features obtained as service execution proceeds. In this paper we investigate several potential software features for suitability during the employment of a cloud service identification system. The generation of stable and unique digital identity from features in Cloud computing is challenging because of the unstable operation environments that implies the features employed are likely to vary under normal operating conditions. To address this, we introduce a multi-dimensional key generation technology which maps from multi-dimensional feature space directly to a key space. Subsequently, a smooth entropy algorithm is developed to evaluate the entropy of key space.
  • Gillham, M. et al. (2013). Floor Covering and Surface Identification for Assistive Mobile Robotic Real-Time Room Localization Application. Sensors [Online] 13:17501-17515. Available at: http://dx.doi.org/10.3390/s131217501.
    Assistive robotic applications require systems capable of interaction in the human world, a workspace which is highly dynamic and not always predictable. Mobile assistive devices face the additional and complex problem of when and if intervention should occur; therefore before any trajectory assistance is given, the robotic device must know where it is in real-time, without unnecessary disruption or delay to the user requirements. In this paper, we demonstrate a novel robust method for determining room identification from floor features in a real-time computational frame for autonomous and assistive robotics in the human environment. We utilize two inexpensive sensors: an optical mouse sensor for straightforward and rapid, texture or pattern sampling, and a four color photodiode light sensor for fast color determination. We show how data relating floor texture and color obtained from typical dynamic human environments, using these two sensors, compares favorably with data obtained from a standard webcam. We show that suitable data can be extracted from these two sensors at a rate 16 times faster than a standard webcam, and that these data are in a form which can be rapidly processed using readily available classification techniques, suitable for real-time system application. We achieved a 95% correct classification accuracy identifying 133 rooms’ flooring from 35 classes, suitable for fast coarse global room localization application, boundary crossing detection, and additionally some degree of surface type identification.
  • Radu, P. et al. (2013). A review of information fusion techniques employed in iris recognition systems. International Journal of Advanced Intelligence Paradigms [Online] 4:211-240. Available at: http://dx.doi.org/10.1504/IJAIP.2012.052067.
    Iris recognition has shown to be one of the most reliable biometric authentication methods. The majority of iris recognition systems which have been developed require a constrained environment to enrol and recognise the user. If the user is not cooperative or the capture environment changes then the accuracy of the iris recognition system may decrease significantly. To minimise the effect of such limitations, possible solutions include the use of multiple channels of information such as using both eyes or extracting more iris feature types and subsequently employing an efficient fusion method. In this paper, we present a review of iris recognition systems using information from multiple sources that are fused in different ways or at different levels. A categorisation of the iris recognition systems incorporating multiple classifier systems is also presented. As a new desirable dimension of a biometric system, besides those proposed in the literature, the mobility of such a system is introduced in this work. The review charts the path towards greater flexibility and robustness of iris recognition systems through the use of information fusion techniques and points towards further developments in the future leading to mobile and ubiquitous deployment of such systems.
  • Radu, P. et al. (2013). A Colour Iris Recognition System Employing Multiple Classifier Techniques. ELCVIA Electronic Letters on Computer Vision and Image Analysis [Online] 12:54-65. Available at: http://elcvia.cvc.uab.es/article/view/520.
    The randomness of iris texture has allowed researchers to develop biometric systems with almost flawless accuracies. However, a common drawback of the majority of existing iris recognition systems is the constrained environment in which the user is enroled and recognized. The iris recognition systems typically require a high quality iris image captured under near infrared illumination. A desirable property of an iris recognition system is to be able to operate on colour images, whilst maintaining a high accuracy. In the present work we propose an iris recognition methodology which is designed to cope with noisy colour iris images. There are two main contributions of this paper: first, we adapt standard iris features proposed in literature for near infrared images by applying a feature selection method on features extracted from various colour channels; second, we introduce a Multiple Classifier System architecture to enhance the recognition accuracy of the biometric system. With a feature size of only 360 real valued components, the proposed iris recognition system performs with a high accuracy on UBIRISv1 dataset, in both identification and verfication scenarios.
  • Sheng, W. et al. (2012). Reliable and Secure Encryption Key Generation from Fingerprints. Information Management & Computer Security [Online] 20:207-221. Available at: http://dx.doi.org/10.1108/09685221211247307.
    Purpose ? Biometric authentication, which requires storage of biometric templates and/or encryption keys, raises a matter of serious concern, since the compromise of templates or keys necessarily compromises the information secured by those keys. To address such concerns, efforts based on dynamic key generation directly from the biometrics have recently emerged. However, previous methods often have quite unacceptable authentication performance and/or small key spaces and therefore are not viable in practice. The purpose of this paper is to propose a novel method which can reliably generate long keys while requires storage of neither biometric templates nor encryption keys. Design/methodology/approach ? This proposition is achieved by devising the use of fingerprint orientation fields for key generation. Additionally, the keys produced are not permanently linked to the orientation fields, hence, allowing them to be replaced in the event of key compromise. Findings ? The evaluation demonstrates that the proposed method for dynamic key generation can offer both good reliability and security in practice, and outperforms other related methods. Originality/value ? In this paper, the authors propose a novel method which can reliably generate long keys while requires storage of neither biometric templates nor encryption keys. This is achieved by devising the use of fingerprint orientation fields for key generation. Additionally, the keys produced are not permanently linked to the orientation fields, hence, allowing them to be replaced in the event of key compromise.

Conference or workshop item

  • Murphy, J., Howells, G. and McDonald-Maier, K. (2018). On Quaternary 1-of-4 ID Generator Circuits. in: IEEE EST 2018. IEEE. Available at: http://dx.doi.org/10.1109/AHS.2018.8541477.
    A quaternary 1-of-4 ID generator circuit is
    presented. It exploits the properties of quaternary metastability
    to provide stable n-bit IDs tolerant to the effects
    of nanoscale process scaling and temperature variations,
    which is achieved by increasing the margin between
    threshold voltage and metastability voltage via quaternary
    metastability. A 128-bit ID generator hardware implementation
    and electrical evaluation yields an average of 26.6%
    uniqueness of ID bits and 100% stability rate over a 10?C
    to 40?C temperature range.
  • Howells, G. and Gillham, M. (2017). Attitude Control of Small Probes for De-orbit, Descent and Surface Impact on Airless Bodies Using a Single PWM Thruster. in: 6th International conference on Space Mission Challenges for Information Technology. IEEE. Available at: http://dx.doi.org/10.1109/SMC-IT.2017.16.
    A single thruster attitude and de-orbital control method is proposed, capable of delivering a small spin stabilized probe with payload to the surface of an airless body such as the Moon. Nutation removal, attitude control and fast large angle maneuvers have been demonstrated and shown to be effective using a commercially available single standard cold gas pulse width modulated controlled thruster model. Maximum final impact angle due to drift and residual velocities was found to be less than 5 degrees and the maximum angle of attack to be 4 deg. The conventional 3-axis control would require as many as twelve thrusters requiring a more substantial structure with complex pipework, and a more sophisticated controller. The single thruster concept minimises the mass requirement and thus cost of the mission, making the concept of small networked surface probes for extended science missions more viable. Experiments based on computer simulation have shown that strict design and mission profile requirements can be fulfilled using the single thruster control method.
  • Murphy, J., Howells, G. and McDonald-Maier, K. (2017). Multi-factor Authentication using Accelerometers for the Internet-of-Things. in: Seventh IEEE International Conference on Emerging Security Technologies. IEEE, pp. 103-107. Available at: https://doi.org/10.1109/EST.2017.8090407.
    Embedded and mobile devices forming part of the Internet-of-Things (IoT) need new authentication technologies and techniques. This requirement is due to the increase in effort and time attackers will use to compromise a device, often remote, based on the possibility of a significant monetary return. This paper proposes exploiting a device’s accelerometers in-built functionality to implement multi-factor authentication. An experimental embedded system designed to emulate a typical mobile device is used to implement the ideas and investigated as proof-of-concept.
  • Stoica, A. et al. (2017). A Holistic Approach to Interpreting Human States in Smart Environments Providing High Quality of Life. in: Seventh IEEE International Conference on Emerging Security Technologies.. Available at: https://doi.org/10.1109/EST.2017.8090412.
    We formulate a concept of a future smart environment for high quality of life (SEQUAL) that would empower humans to compensate for physical and cognitive disabilities associated with sickness and aging. In SEQUAL the assessment of the state of ‘well-being’ - from behaviors and biological signals - is holistic, meaning that the estimation of individual’s health, emotional condition, activity and wishes, are from the beginning determined in relation to each other and in (individual’s own) context, with superior results compared to when estimated independent from each other, as in common practice. Similarly, the prediction of a person’s future condition, intentions, future needs, and actions/treatment/interventions are determined holistically. SEQUAL includes robots, mobility systems and assistive devices for physical intervention, as well as remote professional caregivers, family and friends, to provide intelligent assistance and support network, aiming for higher quality of life for both patient and caregiver.
  • Canoz, V. et al. (2017). Embedded hardware for closing the gap between research and industry in the assistive powered wheelchair market. in: IEEE/SICE International Symposium on System Integration (SII 2016). IEEE. Available at: https://doi.org/10.1109/SII.2016.7843983.
    Literature is abound with smart wheelchair platforms of various developments, yet to date there has been little technology find its way to the market place. Many trials and much research has taken place over the last few decades however the end user has benefited precious little. There exists two fundamental difficulties when developing a smart powered wheelchair assistive system, the first is need for the system to be fully compatible with all of the manufacturers, and the second is to produce a technology and business model which is marketable and therefore desirable to the manufacturers. However this requires the researchers to have access to hardware which can be used to develop practical systems which integrate and communicate seamlessly with current manufacturer’s wheelchair systems. We present our powered wheelchair system which integrates with 95% of the powered wheelchair controller market; our system allows researchers to access the low level embedded system with more powerful computational devices running sophisticated software enabling rapid development of algorithms and techniques. When they have been evaluated they can be easily ported to the embedded processor for real-time evaluation and clinical trial.
  • Ye, B. and Howells, G. (2016). Integrating Multi-Modal Cloud Features within a Multi-Dimensional Encryption Space. in: Sixth International Conference on Emerging Security Technologies.. Available at: http://dx.doi.org/10.1109/EST.2015.12.
    The problem of combining multi-modal features which extract from characteristics of given Cloud Computing Servers in the pattern recognition system is well known difficult. This paper addresses a novel efficient technique for normalizing sets of features which are highly multi-modal in nature, so as to allow them to be incorporated from a multi-dimensional feature distribution space. The intend system identify the modes of each distribution and for removing any possible correlation between the feature data to allow to be used in an encryption key generation system.
  • Sobhy, M., Batchelor, J. and Howells, G. (2016). Identification of Transmitting Antennas in Secure Internet of Things Networks. in: Loughborough Antennas and Propagation Conference LAPC16. Loughborough, pp. 1-3.
    Bluetooth and WIFI channels are open to public users and have few security procedures. One security aspect is for a receiver to be able to verify the identity of the transmitter. This paper describes methods of identifying transmitters by the properties of their antennas.
  • Gillham, M., Howells, G. and Kelly, S. (2016). Assistive trajectories for human-in-the-loop mobile robotic platforms. in: Sixth International Conference on Emerging Security Technologies.. Available at: http://dx.doi.org/10.1109/EST.2015.19.
  • Gillham, M. et al. (2016). Developing Effective Intelligent Assistance for the Powered Wheelchair User. in: Technology for Independence Conference (T4i).. Available at: https://dx.doi.org/10.15131/shef.data.4256522.
    This research is working towards developing a pre-production prototype system which can provide a low-cost real-time adjustable and adaptable driving assistance system for powered wheelchair users. Currently we are seeking to obtain information from user joystick input and their driving quality to identify symptoms and make adjustments to the driving assistance system.
  • Hu, Y., Sirlantzis, K. and Howells, G. (2016). A study on iris textural correlation using steering kernels. in: 8th IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS 2016). IEEE. Available at: https://doi.org/10.1109/BTAS.2016.7791160.
    Research on iris recognition have observed that iris texture
    has inherent radial correlation. However, currently,
    there lacks a deeper insight into iris textural correlation.
    Few research focus on a quantitative and comprehensive
    analysis on this correlation. In this paper, we perform a
    quantitative analysis on iris textural correlation. We employ
    steering kernels to model the textural correlation in images.
    We conduct experiments on three benchmark datasets covering
    iris captures with varying quality. We find that the
    local textural correlation varies due to local characteristics
    in iris images, while the general trend of textural correlation
    goes along the radial direction. Moreover, we demonstrate
    that the information on iris textural correlation can
    be utilized to improve iris recognition. We employ this information
    to produce iris codes. We show that the iris code
    with the information on textural correlation achieves an improved
    performance compared to traditional iris codes.
  • Hu, Y. et al. (2015). An online background subtraction algorithm using contiguously weighted linear regression. in: EUSIPCO 2015 - European Signal Processing Conference.. Available at: http://www.eusipco2015.org/.
  • Hu, Y., Sirlantzis, K. and Howells, G. (2015). Exploiting stable and discriminative iris weight map for iris recognition under less constrained environment. in: 7th IEEE International Conference on Biometrics: Theory, Applications and Systems.
  • Catley, E. et al. (2014). Non-overlapping dual camera fall detection using the NAO humanoid robot. in: 5th International Conference on Emerging Security Technologies. pp. 67-70.
    With an aging population and a greater desire for independence, the dangers of falling incidents in the elderly have become particularly pronounced. In light of this, several technologies have been developed with the aim of preventing or monitoring falls. Failing to strike the balance between several factors including reliability, complexity and invasion of privacy has seen prohibitive in the uptake of these systems. Some systems rely on cameras being mounted in all rooms of a user's home while others require being worn 24 hours a day. This paper explores a system using a humanoid NAO robot with dual vertically mounted cameras to perform the task of fall detection.
  • Ye, B., Haciosman, M. and Howells, G. (2014). Analysis of ICmetrics features requirments in Cloud environment. in: 10th Annual International Conference on Grid and Cloud Computing and Applications.
  • Haciosman, M., Ye, B. and Howells, G. (2014). Protecting and identifiying smartphone apps using ICmetrics. in: 5th International Conference on Emerging Security Technologies.
  • Hu, Y., Sirlantzis, K. and Howells, G. (2014). A Robust Algorithm for Colour Iris Segmentation Based on 1-norm Regression. in: International Joint Conference on Biometrics.
  • Catley, E. et al. (2014). Preliminary investigations into human fall verification in static images using the NAO humanoid robot. in: CareTECH.
  • Zhai, X. et al. (2014). Detecting Compromised Programs for Embedded System Applications: 27th International Conference, Lübeck, Germany, February 25-28, 2014. Proceedings. in: Architecture of Computing Systems, ARCS 2014. Springerlink, pp. 221-232. Available at: http://dx.doi.org/10.1007/978-3-319-04891-8_19.
    This paper proposes an approach for detecting compromised programs by analysing suitable features from an embedded system. Features used in this paper are the performance variance and actual program counter values of the embedded processor extracted during program execution. “Cycles per Instruction” is used as pre-processing block before the features are classified using a Self-Organizing Map. Experimental results demonstrate the validity of the proposed approach on detecting some common changes such as deletion, insertion and substitution of programs. Overall, correct detection rate for our system is above 90.9% for tested programs.
  • Appiah, K. et al. (2013). Program Counter as an Integrated Circuit Metrics for Secured Program Identification. in: 4th International Conference on Emerging Security Technologies (EST 2013),. IEEE, pp. 98-101. Available at: http://dx.doi.org/10.1109/EST.2013.23.
    Integrated Circuit Metrics is mainly concerned with the extraction of measurable properties or features of a given hardware device, capable of uniquely identifying the system's behaviour. This paper presents features that can be extracted from software executing on a device and identify the very software in execution. The main contribution of this paper is in two folds. The ability to extract features whiles the software is in execution as well as correctly identifying the software to divulge any tampering or malicious exploitation. Our aim is to use program counter values generated during program execution to train a k-means algorithm optimized for vector quantization, and later use the system to associate program counter values with an application.
  • Tahir, R. et al. (2013). Resilience against Brute Force and Rainbow Table Attacks using Strong ICMetrics Session Key Pairs. in: IEEE. Available at: http://www.dx.doi.org/ 10.1109/ICCSPA.2013.6487307.
    Cryptography has become an essential for providing security in embedded system applications. The employed cryptographic primitives should provide strong protection such that the security of the system is not compromised at any point in the lifecycle of a secure operation. This particularly includes the secure generation and maintenance of cryptographic keys. In general this assumption is difficult to accomplish, since there are attacks that come under this umbrella ranging from brute force attacks on the key to capturing the node to extract the key. In this paper we investigate and analyze ICMetrics and its counterpart scheme referred to as the scheme for the generation of strong high entropy ICMetrics session key pairs. ICMetrics is a key technology that computes the secret key based on hardware/ software properties of a device, thereby providing resilience against node capture attacks, while high entropy key pair generation scheme is employed to strengthen the generated ICMetrics basis number, so as to safeguard the generated strong key pairs from brute force and rainbow table attacks.
  • Tahir, R. et al. (2013). A Scheme for the Generation of Strong ICMetrics based Session Key Pairs for Secure Embedded System Applications. in: The First International Conference on Communications, Signal Processing and their applications. IEEE. Available at: http://www.dx.doi.org/ 10.1109/WAINA.2013.143.
    This paper presents a scheme for the generation of strong session based ICMetrics key pairs for security critical embedded system applications. ICMetrics generates the security attributes of the sensor node based on measurable hardware and software characteristics of the integrated circuit. In the proposed scheme a random session ID is assigned by a trusted party to each participating network entity, which remains valid for a communication session. Our work is based on the design of a key derivation function that uses an ICMetrics secret key and a session token assigned by the trusted party to derive strong cryptographic key pairs for each entity. These session tokens also serve the purpose of identification/authentication between the trusted parties and the respective nodes in each network. The main strength of our proposed scheme rests on the randomness feature incorporated via the random session ID's, which makes the generated strong private/public key pair highly resistant against exhaustive search and rainbow table attacks. Our proposed approach makes use of key stretching using random session tokens via SHA-2 and performs multiple iterations of the proposed key derivation function to generate strong high entropy session key pairs of sufficient length. The randomness of the assigned ID's and the session based communication hinders the attacker's ability to launch various sorts of cryptanalytic attacks, thereby making the generated keys very high in entropy. The randomness feature has also been very carefully tuned according to the construction principles of ICMetrics, so that it doesn't affect the original ICMetrics data. The second part of the proposed scheme generates a corresponding public session key by computing the Hermite Normal Form of the high entropy private session key.
  • Zhai, X. et al. (2013). A Self-Organising Map Based Algorithm for Analysis of ICmetrics Features. in: 4th International Conference on Emerging Security Technologies (EST 2013),. IEEE, pp. 93-97. Available at: http://dx.doi.org/10.1109/EST.2013.22.
    ICmetrics is a new approach that exploits the characteristic and behaviour of an embedded system to obtain a collection of properties and features, which aims to uniquely identify and secure an embedded system based on its own behavioural identity. In this paper, an algorithm based on a self-organising map (SOM) neural network is proposed to extract and analyse the features derived from a processor's performance profile (i.e. average cycles per instruction (CPI)), where the extracted features are used to help finding the main behaviours of the system. The proposed algorithm has been tested with different programs selected from the MiBench benchmark suite, and the results achieved show that it can successfully segment each program into different main phases based on the unique extracted features, which confirms its utility for the ICmetrics technology.
  • Zhai, X. et al. (2013). Application of ICmetrics for Embedded System Security. in: 4th International Conference on Emerging Security Technologies. IEEE, pp. 89-92. Available at: http://dx.doi.org/10.1109/EST.2013.21.
    Integrated Circuit Metrics (ICmetrics) technology is concerned with the extraction of measurable features of an embedded system, capable of uniquely identifying the system's behaviour. Any changes in these identifiers (profiles) during consequent devices' operation would signal about a possible safety or security breach within the electronic system. This paper explores the combination of program counter (PC) and Cycles per Instructions (CPI) of a processor core as a potential ICmetrics source for embedded system security. The use of this combination exhibits that while isolated PC values may not always generate a stable identifier (profile) for a device that would distinguish the device from the rest in a considered set, the PC and CPI sequences and frequencies in the execution flow may serve as suitable ICmetrics features.
  • Ye, B., Howells, G. and Haciosman, M. (2013). Investigation of Properties of ICmetric in Cloud. in: 4th International Conference on Emerging Security Technologies (EST 2013),. IEEE, pp. 107-108. Available at: http://dx.doi.org/10.1109/EST.2013.36.
    This paper investigates some practical aspects of the employment of measurable features derived from characteristics of given Cloud computing servers for the generation of encryption keys pertaining to the servers, a technique termed ICmetric. The ICmetric technology requires identifying the suitable features in a distributed environment for encryption purpose. Ideally, the nature of the features should be identical for all of the systems considered, while the values of these features should allow for unique identification of each of the system servers. This paper looks at the properties of the server behaviors as a potential ICmetric feature, and explores how the number of its samples being inputted into the ICmetric system affects stability of the system's performance.
  • Gillham, M. et al. (2013). Real-time Doorway Detection and Alignment Determination for Improved Trajectory Generation in Assistive Mobile Robotic Wheelchairs. in: Emerging Security Technologies (EST), 2013 Fourth International Conference on. pp. 62-65.
    Powered wheelchair users may find operation in enclosed environments such as buildings difficult; a fundamental problem exists: wheelchairs are not much narrower than the doorway they wish to pass through. The ability to detect and pass through doorways represents a major current challenge for automated guided wheelchairs. We utilize a simple doorway pattern recognition technique for fast processing in a real-time system for robotic wheelchair users. We are able to show a 96% detection and identification of 5 individual doorways and an 86% recognition rate of 22 separate approach angles and translations. We conclude that pattern recognition using features obtained from simple constrained infrared ranging sensor data binning can be utilized for fast identification of doorways, and important coarse position and approach angle determination, suitable for real-time trajectory adjustment, representing a significant enhancement in this area.
  • Radu, P. et al. (2013). Optimizing 2D Gabor Filters for Iris Recognition. in: 4th International Conference on Emerging Security Technologies (EST 2013),. IEEE, pp. 47-50. Available at: http://dx.doi.org/10.1109/EST.2013.15.
    The randomness and richness present in the iris texture make the 2D Gabor filter bank analysis a suitable technique to be used for iris recognition systems. To accurately characterize complex texture structures using 2D Gabor filters it is necessary to use multiple sets of parameters of this type of filters. This paper proposes a technique of optimizing multiple sets of 2D Gabor filter parameters to gradually enhance the accuracy of an iris recognition system. The proposed methodology is suitable to be applied on both near infrared and visible spectrum iris images. To illustrate the efficiency of the filter bank design technique, UBIRISv1 database was used for benchmarking
  • Radu, P. et al. (2013). A Multi-algorithmic Colour Iris Recognition System. in: Proceedings of the 5th International Workshop Soft Computing Applications (SOFA). Springer Berlin Heidelberg, pp. 45-56. Available at: http://dx.doi.org/10.1007/978-3-642-33941-7_7.
    The reported accuracies of iris recognition systems are generally higher on near infrared images than on colour RGB images. To increase a colour iris recognition system’s performance, a possible solution is a multialgorithmic approach with an appropriate fusion mechanism. In the present work, this approach is investigated by fusing three algorithms at the score level to enhance the performance of a colour iris recognition system. The contribution of this paper consists of proposing 2 novel feature extraction methods for colour iris images, one based on a 3-bit encoder of the 8 neighborhood and the other one based on gray level co-occurrence matrix. The third algorithm employed uses the classical Gabor filters and phase encoding for feature extraction. A weighted average is used as a matching score fusion. The efficiency of the proposed iris recognition system is demonstrated on UBIRISv1 dataset.
  • Ragot, N. et al. (2013). Enhancing the Autonomy of Disabled Persons: Assistive Technologies Directed by User Feedback. in: 4th International Conference on Emerging Security Technologies (EST 2013),. IEEE, pp. 71-74. Available at: http://dx.doi.org/10.1109/EST.2013.20.
    Europe faces a major and growing healthcare problem due to increase in population, increasing longevity and an aging population with disability. Such dependent, elderly, disabled and vulnerable persons, are concerned since they wish to live at home as long as possible. This aspiration is also shared by national policies and communities across EU. To ensure the optimum care of dependent people, innovative solutions are encouraged to maintain independent life style. This paper outlines two projects, SYSIASS and COALAS, which aim to develop a set of technology based solutions to meet the needs and empower these people by enhancing mobility and communication.
  • Radu, P. et al. (2013). A Novel Iris Clustering Approach Using LAB Color Features. in: 4th IEEE International Symposium on Electrical And Electronics Engineering (ISEEE 2013). IEEE, pp. 1-4. Available at: http://dx.doi.org/10.1109/ISEEE.2013.6674362.
    Interesting results of color clustering for the iris images in the UBIRISv1 database are presented. The iris colors are characterized by feature vectors with 80 components corresponding to histogram bins computed in the CIELAB color space. The feature extraction is applied to the first session eye images after undergoing an iris segmentation process. An agglomerative hierarchical algorithm is used to organize 1.205 segmented iris images in 8 clusters based on their color content.
  • Cheung, W. et al. (2012). Model Driven Development Approach for Effective SOA Communication Performance Analysis. in: UK Electronics Forum.
  • Radu, P. et al. (2012). Image Enhancement vs Feature Fusion in Colour Iris Recognition. in: Emerging Security Technologies (EST), 2012 Third International Conference. IEEE, pp. 53-57. Available at: http://dx.doi.org/10.1109/EST.2012.33.
    In iris recognition, most of the research was conducted on operation under near infrared illumination. For an iris recognition system to be deployed on common hardware devices, such as laptops or mobile phones, its ability of working with visible spectrum iris images is necessary. Two of the main possible approaches to cope with noisy images in a colour iris recognition system are either to apply image enhancement techniques or to extract multiple types of features and subsequently to employ an efficient fusion mechanism. The contribution of the present paper consists of comparing which of the two above mentioned approaches is best in both identification and verification scenarios of a colour iris recognition system. The efficiency of the two approaches is demonstrated on UBIRISv1 dataset
  • Tahir, R. et al. (2012). A Scheme for the Generation of Strong Cryptographic Key Pairs based on ICMetrics. in: The Seventh International Conference for Internet Technology and Secured Transactions (ICITST).
    This paper presents a scheme for the generation of strong high entropy keys based on ICMetrics. ICMetrics generates the security attributes of the sensor node based on measurable hardware and software characteristics of the integrated circuit. This work is based on key derivation functions to derive cryptographic key pairs from ICMetrics values. The proposed ICMetrics based key derivation function makes use of ICMetrics basis numbers and authentication tokens from the trusted third party to generate high entropy public/private key pairs. The proposed approach makes use of key stretching using SHA-2 and performs multiple iterations of the proposed key derivation function to generate strong high entropy keys of sufficient length, so as to prevent exhaustive search attacks. The novelty of this work lies in the fact that the entire key generation scheme has been designed keeping in mind the construction principles of ICMetrics, which does not store keys but computes these for every session based on ICMetrics value, therefore use of a random value anywhere in the protocol will compromise the purpose of ICMetrics. The proposed scheme generates high entropy key pairs while concealing the original ICMetrics data, such that it is impossible to recover the ICMetrics basis data in the system.
  • Aldosary, S. and Howells, G. (2012). A Robust Multimodal Biometric Security System Using the Polynomial Curve Technique within Shamir's Secret Sharing Algorithm. in: Third International Conference on Emerging Security Technologies (EST), 2012. pp. 66-69. Available at: http://dx.doi.org/10.1109/EST.2012.9.
    This paper investigates the application of secret sharing technology to allow an encryption key to be derived from multimodal biometric samples. Within the proposed scheme, individual points on a parabolic curve are indirectly derived from individual biometric samples taken from an individual, and Shamir's Secret Sharing algorithm is applied in order to derive the required key. The proposal is robust, in that a pre-defined subset of modalities is required in order to derive the key, rendering the system able to accommodate exception handling for given modalities. The current paper reports preliminary work on how secret sharing techniques may be employed to integrate arbitrary points that may be derived from the actual biometric data.
  • Kovalchuk, Y. et al. (2012). Investigation of Properties of ICmetrics Features. in: 2012 Third International Conference on Emerging Security Technologies. IEEE, pp. 115-120. Available at: http://dx.doi.org/10.1109/EST.2012.22.
    The ICmetrics technology is concerned with identifying acceptable features in an electronic system's operation for encryption purposes. Ideally, the nature of the features should be identical for all of the systems considered, while the values of these features should allow for unique identification of each of the systems. This paper looks at the properties of the Program Counter of a processor core as a potential ICmetrics feature, and explores how the number of its samples being inputted into the ICmetrics system affects stability of the system's performance.
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