Professor Gareth Howells
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.
Showing 50 of 210 total publications in the Kent Academic Repository. View all publications.
Gillham, M., Pepper, M., Kelly, S. and Howells, G. (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.
Gillham, M., Pepper, M., Kelly, S. and Howells, G. (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
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., Sirlantzis, K., Howells, G., Ragot, N. and Rodriguez, P. (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
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). 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.
Ye, B., Howells, G., Haciosman, M. and Wang, F. (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.
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.
Zhai, X., Appiah, K., Ehsan, S., Howells, G., Hu, H., Gu, D. and McDonald-Maier, K. (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.
Zhai, X., Appiah, K., Ehsan, S., Howells, G., Hu, H., Gu, D. and McDonald-Maier, K. (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.
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.
Gillham, M., Howells, G., Spurgeon, S. and McElroy, B. (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., Sirlantzis, K., Howells, G., Hoque, S. and Deravi, F. (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.
Zhai, X., Appiah, K., Ehsan, S., Cheung, W., Howells, G., Hu, H., Gu, D. and McDonald-Maier, K. (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 27th International Conference. Cham, Switzerland: Springer, 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.
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., Iwashita, Y., Assad, C., Ryoo, M. and Howells, G. (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., Gillham, M., Oprea, P., Chaumont, P., Bodin, A., Laux, P., Lebigre, M., Howells, G. and Sirlantzis, K. (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.
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.
Gillham, M., Howells, G., Pepper, M. and Kelly, S. (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.
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.
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.
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.
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.
Hu, Y., Sirlantzis, K., Howells, G., Nicolas, R. and Rodriguez, P. (2015). An online background subtraction algorithm using contiguously weighted linear regression. In: EUSIPCO 2015 - European Signal Processing Conference. Available at: http://www.eusipco2015.org/.
Catley, E., Sirlantzis, K., Howells, G. and Kelly, S. (2014). Preliminary investigations into human fall verification in static images using the NAO humanoid robot. In: CareTECH.
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., Sirlantzis, K., Kelly, S. and Howells, G. (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.
Haciosman, M., Ye, B. and Howells, G. (2014). Protecting and identifiying smartphone apps using ICmetrics. In: 5th International Conference on Emerging Security Technologies.
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.
Radu, P., Sirlantzis, K., Howells, G., Hoque, S. and Deravi, F. (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
Zhai, X., Appiah, K., Ehsan, S., Hu, H., Gu, D., McDonald-Maier, K., Cheung, W. and Howells, G. (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.
Zhai, X., Appiah, K., Ehsan, S., Cheung, W., Hu, H., Gu, D., McDonald-Maier, K. and Howells, G. (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.
Appiah, K., Zhai, X., Ehsan, S., Cheung, W., Hu, H., Gu, D., McDonald-Maier, K. and Howells, G. (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.
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.
Ragot, N., Bouzbouz, F., Khemmar, R., Ertaud, J., Kokosy, A., Labbani-Igbida, O., Sajous, P., Niyonsaba, E., Reguer, D., Hu, H., McDonald-Maier, K., Sirlantzis, K., Howells, G., Pepper, M. and Sakel, M. (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.
Spanogianopoulos, S. (2017). A New Approach towards Non-Holonomic Path Planning of Car-Like Robots Using Rapidly Random Tree Fixed Nodes(RRT*FN).Autonomous car driving is gaining attention in industry and is also an ongoing research in scientific community. Assuming that the cars moving on the road are all autonomous, this thesis introduces an elegant approach to generate non-holonomic collision-free motion of a car connecting any two poses (configurations) set by the user. Particularly this thesis focusses research on "path-planning" of car-like robots in the presence of static obstacles.
Path planning of car-like robots can be done using RRT and RRT*. Instead of generating the non-holonomic path between two sampled configurations in RRT, our approach finds a small incremental step towards the next random configuration. Since the incremental step can be in any direction we use RRT to guide the robot from start configuration to end configuration.
This "easy-to-implement" mechanism provides flexibility for enabling standard plan- ners to solve for non-holonomic robots without much modifications. Thus, strength of such planners for car path planning can be easily realized. This thesis demon- strates this point by applying this mechanism for an effective variant of RRT called as RRT - Fixed Nodes (RRT*FN).
Experiments are conducted by incorporating our mechanism into RRT*FN (termed as RRT*FN-NH) to show the effectiveness and quality of non-holonomic path gener- ated. The experiments are conducted for typical benchmark static environments and the results indicate that RRT*FN-NH is mostly finding the feasible non-holonomic solutions with a fixed number of nodes (satisfying memory requirements) at the cost of increased number of iterations in multiples of 10k.
Thus, this thesis proves the applicability of mechanism for a highly constrained planner like RRT*-FN, where the path needs to be found with a fixed number of nodes. Although, comparing the algorithm (RRT*FN-NH) with other existing planners is not the focus of this thesis there are considerable advantages of the mechanism when applied to a planner. They are a) instantaneous non-holonomoic path generation using the strengths of that particular planner, b) ability to modify on-the-fly non-holomic paths, and c) simple to integrate with most of the existing planners.
Moreover, applicability of this mechanism using RRT*-FN for non-holonomic path generation of a car is shown for a more realistic urban environments that have typical narrow curved roads. The experiments were done for actual road map obtained from google maps and the feasibility of non-holonomic path generation was shown for such environments. The typical number of iterations needed for finding such feasible solutions were also in multiple of 10k. Increasing speed profiles of the car was tested by limiting max speed and acceleration to see the effect on the number of iterations.
Hu, Y. (2017). Improving Less Constrained Iris Recognition.The iris has been one of the most reliable biometric traits for automatic human authentication due to its highly stable and distinctive patterns. Traditional iris recognition algorithms have achieved remarkable performance in strictly constrained environments, with the subject standing still and with the iris captured at a close distance. This enables the wide deployment of iris recognition systems in applications such as border control and access control. However, in less constrained environments with the subject at-a-distance and on-the-move, the iris recognition performance is significantly deteriorated, since such environments induce noise and degradations in iris captures. This restricts the applicability and practicality of iris recognition technology for some real-world applications with more open capturing conditions, such as surveillance, forensic and mobile device security applications. Therefore, robust algorithms for less constrained iris recognition are desirable for the wider deployment of iris recognition systems.
This thesis focuses on improving less constrained iris recognition. Five methods are proposed to improve the performance of different stages in less constrained iris recognition. First, a robust iris segmentation algorithm is developed using l1-norm regression and model selection. This algorithm formulates iris segmentation as robust l1-norm regression problems. To further enhance the robustness, multiple segmentation results are produced by applying l1-norm regression to different models, and a model selection technique is used to select the most reliable result. Second, an iris liveness detection method using regional features is investigated. This method seeks not only low level features, but also high level feature distributions for more accurate and robust iris liveness detection. Third, a signal-level information fusion algorithm is presented to mitigate the noise in less constrained iris captures. With multiple noisy iris captures, this algorithm proposes a sparse-error low rank matrix factorization model to separate noiseless iris structures and noise. The noiseless structures are preserved and emphasised during the fusion process, while the noise is suppressed, in order to obtain more reliable signals for recognition. Fourth, a method to generate optimal iris codes is proposed. This method considers iris code generation from the perspective of optimization. It formulates traditional iris code generation method as an optimization problem; an additional objective term modelling the spatial correlations in iris codes is applied to this optimization problem to produce more effective iris codes. Fifth, an iris weight map method is studied for robust iris matching. This method considers both intra-class bit stability and inter-class bit discriminability in iris codes. It emphasises highly stable and discriminative bits for iris matching, enhancing the robustness of iris matching.
Comprehensive experimental analysis are performed on benchmark datasets for each of the above methods. The results indicate that the presented methods are effective for less constrained iris recognition, generally improving state-of-the-art performance.
Ye, B. (2016). Encryption Key Generation InCloud Environments.Protecting Cloud services located within the Cloud Computing centre easily would be a significant advantage in the current Cloud computing market. However, the existing encryption system all process a notable weakness that the private key must be stored locally, so could be accessed and used to break the encryption. To solve this problem, a novel technology has been investigated that recompose the private key by using the properties and behaviours extracted from a Cloud server during execution. This thesis will investigate the feasibility of this approach by analysing simple online programs which would typically form the basis or components of larger systems and thereby indicate, by the ability to distinguish such simple systems, which larger real world practical systems may also be distinguished. The private key does not need to store in the system, which this paper has proved such a system is feasible to be applied in the current encryption system.
Aldosary, S. (2015). Investigation of Multimodal Template-Free Biometric Techniques and Associated Exception Handling.The Biometric systems are commonly used as a fundamental tool by both government and private sector organizations to allow restricted access to sensitive areas, to identify the criminals by the police and to authenticate the identification of individuals requesting to access to certain personal and confidential services. The applications of these identification tools have created issues of security and privacy relating to personal, commercial and government identities. Over the last decade, reports of increasing insecurity to the personal data of users in the public and commercial domain applications has prompted the development of more robust and sound measures to protect the personal data of users from being stolen and spoofing. The present study aimed to introduce the scheme for integrating direct and indirect biometric key generation schemes with the application of Shamir‘s secret sharing algorithm in order to address the two disadvantages: revocability of the biometric key and the exception handling of biometric modality. This study used two different approaches for key generation using Shamir‘s secret sharing scheme: template based approach for indirect key generation and template-free. The findings of this study demonstrated that the encryption key generated by the proposed system was not required to be stored in the database which prevented the attack on the privacy of the data of the individuals from the hackers. Interestingly, the proposed system was also able to generate multiple encryption keys with varying lengths. Furthermore, the results of this study also offered the flexibility of providing the multiple keys for different applications for each user. The results from this study, consequently, showed the considerable potential and prospect of the proposed scheme to generate encryption keys directly and indirectly from the biometric samples, which could enhance its success in biometric security field.
Gillham, M. (2015). A Non-Holonomic, Highly Human-in-the-Loop Compatible, Assistive Mobile Robotic Platform Guidance Navigation and Control Strategy.The provision of assistive mobile robotics for empowering and providing independence to the infirm, disabled and elderly in society has been the subject of much research. The issue of providing navigation and control assistance to users, enabling them to drive their powered wheelchairs effectively, can be complex and wide-ranging; some users fatigue quickly and can find that they are unable to operate the controls safely, others may have brain injury re-sulting in periodic hand tremors, quadriplegics may use a straw-like switch in their mouth to provide a digital control signal.
Advances in autonomous robotics have led to the development of smart wheelchair systems which have attempted to address these issues; however the autonomous approach has, ac-cording to research, not been successful; users reporting that they want to be active drivers and not passengers. Recent methodologies have been to use collaborative or shared control which aims to predict or anticipate the need for the system to take over control when some pre-decided threshold has been met, yet these approaches still take away control from the us-er. This removal of human supervision and control by an autonomous system makes the re-sponsibility for accidents seriously problematic.
This thesis introduces a new human-in-the-loop control structure with real-time assistive lev-els. One of these levels offers improved dynamic modelling and three of these levels offer unique and novel real-time solutions for: collision avoidance, localisation and waypoint iden-tification, and assistive trajectory generation. This architecture and these assistive functions always allow the user to remain fully in control of any motion of the powered wheelchair, shown in a series of experiments.
Murphy, J., Howells, G. and McDonald-Maier, K. (2019). A Machine Learning Method For Sensor Authentication Using Hidden Markov Models. In: Eighth IEEE International Conference on Emerging Security Technologies. Available at: https://eis.essex.ac.uk/EST2019/.A machine learning method for sensor based authentication is presented. It exploits hidden markov models to generate stable and synthetic probability density functions from variant sensor data. The principle, and novelty, of the new method are presented in detail together with a statistical evaluation. The results show a marked improvement in stability through the use of hidden markov models.
Baba, S., Yadav, S. and Howells, G. (2019). SortAlgo-Metrics: Identification of Cloud-Based Server Via a Simple Algorithmic Analysis. In: Eighth IEEE International Conference on Emerging Security Technologies. Available at: https://eis.essex.ac.uk/EST2019/.This paper introduces a novel technique to detect spoof or fake software systems via the generation of a unique digital signature based on a direct analysis of the construction of the system. Specifically, we model a novel mechanism referred to as SortAlgo-Metrics analysis to identify cloud-based servers. Experimentally, we deployed four cloud-based servers to run four sorting algorithms in order to extract features that are employed to perform statistical analysis upon with the aim to obtain their metrics which has further underpin the investigation of their behaviours. The model has been validated by comparing training data and unknown data, and the result has shown server 2-4 have a strong identification with 96% probability, while server 1 with 55%, it is surmised that is could be as the result of insufficient sample data. However, if such a simple model can produce a result with this high probability, this shows that with more complex features and sufficient data pulled from cloud-based servers, SortAlgo-Metrics model could generate a higher degree of basis numbers for ICMetrics technology entropy key generation and other complex systems.
Yadav, S. and Howells, G. (2019). Secure device identification using multidimensional mapping. In: Eighth IEEE International Conference on Emerging Security Technologies. Available at: https://eis.essex.ac.uk/EST2019/.In this paper we investigate several potential hardware features from multiple devices for suitability during the employment of a device identification. The generation of stable and unique digital identity from features is challenging in device identification 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 novel multi-dimensional key generation technology which maps from multi-dimensional feature space directly to a key space. Furthermore, normalized distributions of features give the necessary data to model the characteristics, from which we derive intra-sample device feature distributions, and correlate the distinct features to generate a secure key to identify the device. Furthermore, to evaluate our experiment, we considerably carried out measurement using the mathematical & statistical modelling.
Oprea, P., Sirlantzis, K., Chatzidimitriadis, S., Doumas, O. and Howells, G. (2019). Artificial intelligence for safe assisted driving based on user head movements in robotic wheelchairs. In: 15th Conference on Global Challenges in Assistive Technology: Research, Policy & Practice. Available at: https://aaate2019.eu/.Wheelchairs users don’t always have the ability to control a powered wheelchair using a normal joystick due to factors that restrict the use of their arms and hands. For a certain number of these individuals, which still retain mobility of their head, alternative methods have been devised, such as chin-joysticks, head switches or sip-and-puff control. Such solutions can be bulky, cumbersome, unintuitive or simply uncomfortable and taxing for the user. This work presents an alternative head-based drive-control system for wheelchair users.
Mohamed, E., Dib, J., Sirlantzis, K. and Howells, G. (2019). Integrating ride dynamics measurements and user comfort assessment to smart robotic wheelchairs. In: 15th Conference on Global Challenges in Assistive Technology: Research, Policy & Practice. Available at: https://aaate2019.eu/.Individuals relying on wheelchairs for mobility are subject to the risk of injury due to their exposure to whole-body vibrations for long periods of time as per ISO 2631-1. Our study evaluates the feasibility of integrating ride dynamics measurements (i.e. vertical accelerations) as expressions of user travel comfort assessment to smart robotic wheelchairs. This will also help to mitigate the injury risk caused by the continuous exposure to vibrations using real time electronic measurement systems in order to ensure that the wheelchair’s movement dynamics (acceleration and speed) and the user’s comfort is adapted to the surrounding environment, specifically the type of ground surface type, as per the ISO standard mentioned previously.
Mohamed, E., Sirlantzis, K. and Howells, G. (2019). Application of Transfer Learning for Object Detection on Manually Collected Data. In: Intelligent Systems Conference (IntelliSys) 2019. Available at: https://saiconference.com/IntelliSys.This paper investigates the usage of pre-trained deep learning neural networks for object detection on a manually collected dataset for real-life indoor objects. Availability of object-specific datasets is a great challenge and the unavoidable task of collecting, processing and annotating ground truth data is laborious and time-consuming. In this paper, two famous models (AlexNet and Vgg16) have been evaluated as feature extractors in a Faster R-CNN network. Network models have been trained end-to-end on the collected dataset. The study highlights the poor performance of state of art systems when dealing with small size objects. Modifying the detector design by redesigning systems’ anchor boxes might help to tackle this problem. Detector results on the proposed dataset have been collected and compared. In addition, limitations and future work have been discussed.
Khalid, A., Saha, S., Bhatt, B., Gu, D., Howells, G. and McDonald-Maier, K. (2019). FLAG: A Framework for FPGA Based Load Generator in Profinet Communication. In: International Conference on Industry 4.0 and Artificial Intelligence Technologies. Available at: https://inait-conf.org/.Like other automated system technologies, PROFINET, a real-time Industrial Ethernet Standard has shown increasing level of
integration into the present IT Infrastructure. Such vast use of PROFINET can expose the controllers and I/O devices to operate in
critical failures when traffic goes unexpectedly higher than normal. Rigorous testing of the running devices then becomes essential
and therefore, in this paper, we prototype and design an FPGA based load Generating solution called “FLAG (FPGA based LoAd
Generator) for PROFINET based traffic at the desired load configurations such as, bits per second, the number and size of the
packets with their Ethertypes and MAC addresses. We have employed, a Zynq-7000 FPGA as our implementation platform for
the proposed FLAG framework. The system can easily be deployed and accessed via the web or command line interface for
successful load generation. Extensive experiments have been conducted to verify the effectiveness of our proposed solution and
the results confirm that the proposed framework is capable to generate precise load at Fast/Gigabit line rate with a defined number