All Outputs (2071)

GLASS: Towards Secure and Decentralized eGovernance Services using IPFS (2022)
Presentation / Conference Contribution
Chrysoulas, C., Thomson, A., Pitropakis, N., Papadopoulos, P., Lo, O., Buchanan, W. J., Domalis, G., Karacapilidis, N., Tsakalidis, D., & Tsolis, D. (2021, October). GLASS: Towards Secure and Decentralized eGovernance Services using IPFS. Presented at 7th Workshop On The Security Of Industrial Control Systems & Of Cyber-Physical Systems (CyberICPS 2021). In Conjunction With ESORICS 2021, Darmstadt, Germany

The continuously advancing digitization has provided answers to the bureaucratic problems faced by eGovernance services. This innovation led them to an era of automation, broadened the attack surface and made them a popular target for cyber attacks.... Read More about GLASS: Towards Secure and Decentralized eGovernance Services using IPFS.

A Privacy-Preserving Platform for Recording COVID-19 Vaccine Passports (2022)
Presentation / Conference Contribution
Barati, M., Buchanan, W. J., Lo, O., & Rana, O. (2021, December). A Privacy-Preserving Platform for Recording COVID-19 Vaccine Passports. Presented at 14th IEEE/ACM International Conference on Utility and Cloud Computing, Leicester

Digital vaccination passports are being proposed by various governments internationally. Trust, scalability and security are all key challenges in implementing an online vaccine passport. Initial approaches attempt to solve this problem by using cent... Read More about A Privacy-Preserving Platform for Recording COVID-19 Vaccine Passports.

Exploring the Need For an Updated Mixed File Research Data Set (2022)
Presentation / Conference Contribution
Davies, S. R., Macfarlane, R., & Buchanan, W. J. (2021, October). Exploring the Need For an Updated Mixed File Research Data Set. Presented at 2021 International Conference on Engineering and Emerging Technologies (ICEET), Istanbul, Turkey

Mixed file data sets are used in a variety of research areas, including Digital Forensics, Malware analysis and Ransomware detection. Researchers recently seem to either have to create their own custom data sets or well-known data sets are used, but... Read More about Exploring the Need For an Updated Mixed File Research Data Set.

Review of Current Ransomware Detection Techniques (2022)
Presentation / Conference Contribution
Davies, S. R., Macfarlane, R., & Buchanan, W. J. (2021, October). Review of Current Ransomware Detection Techniques. Presented at 2021 International Conference on Engineering and Emerging Technologies (ICEET), Istanbul, Turkey

A review of proposed ransomware detection tools and techniques. The tools are described, compared and contrasted and possible short comings in their approaches are discussed.

Tracking Stream Quality Issues in Combined Physical and Radar Sensors for IoT-based Data-driven Actuation (2021)
Presentation / Conference Contribution
Bamgboye, O., Liu, X., Cruickshank, P., Liu, Q., & Zhang, Y. (2021, December). Tracking Stream Quality Issues in Combined Physical and Radar Sensors for IoT-based Data-driven Actuation. Presented at 2021 CIE International Conference on Radar (Radar), Haikou, Hainan, China

In this paper, a stream quality tracking for measurements from combined radar and physical sensors is developed. The authors proposed the use of RDF stream processing system and semantic rules to provide semantic reasoning for tracking erroneous data... Read More about Tracking Stream Quality Issues in Combined Physical and Radar Sensors for IoT-based Data-driven Actuation.

The Task2Dial Dataset: A Novel Dataset for Commonsense-enhanced Task-based Dialogue Grounded in Documents (2021)
Presentation / Conference Contribution
Strathearn, C., & Gkatzia, D. (2021, November). The Task2Dial Dataset: A Novel Dataset for Commonsense-enhanced Task-based Dialogue Grounded in Documents. Presented at 4th International Conference on Natural Language and Speech Processing (ICNLSP 2021), Trento, Italy [Online]

This paper describes the Task2Dial dataset, a novel dataset of document-grounded task-based dialogues in the food preparation domain , where an Information Giver (IG) provides instructions to an Information Follower (IF) so that the latter can succes... Read More about The Task2Dial Dataset: A Novel Dataset for Commonsense-enhanced Task-based Dialogue Grounded in Documents.

The Tree and The Room: Co-Designing DIY WiFi Networks with Emergent Local Metaphors (2021)
Presentation / Conference Contribution
Smyth, M., Helgason, I., Lapidge, L., & Hausel, K. (2021). The Tree and The Room: Co-Designing DIY WiFi Networks with Emergent Local Metaphors. In Design Culture(s) | Cumulus Conference Proceedings Roma 2021, Volume #2 (3823-3837)

The use of metaphor for communicating conceptual models of interactive systems has a well-documented history in Interaction Design practice. Although metaphors can primarily be understood as linguistic devices, designers incorporate t... Read More about The Tree and The Room: Co-Designing DIY WiFi Networks with Emergent Local Metaphors.

Using Semantic Technology to Model Persona for Adaptable Agents (2021)
Presentation / Conference Contribution
Nguyen, J., Farrenkopf, T., Guckert, M., Powers, S., & Urquhart, N. (2021, June). Using Semantic Technology to Model Persona for Adaptable Agents. Presented at ECMS 2021

In state of the art research a growing interest in the application of agent models for the simulation of road traffic can be observed. Software agents are particularly suitable for the representation of travellers and their goal-oriented behaviour. A... Read More about Using Semantic Technology to Model Persona for Adaptable Agents.

Chefbot: A Novel Framework for the Generation of Commonsense-enhanced Responses for Task-based Dialogue Systems (2021)
Presentation / Conference Contribution
Strathearn, C., & Gkatzia, D. (2021). Chefbot: A Novel Framework for the Generation of Commonsense-enhanced Responses for Task-based Dialogue Systems. In Proceedings of the 14th International Conference on Natural Language Generation (46-47)

Conversational systems aim to generate responses that are accurate, relevant and engaging, either through utilising neural end-to-end models or through slot filling. Human-to-human conversations are enhanced by not only the latest utterance of the in... Read More about Chefbot: A Novel Framework for the Generation of Commonsense-enhanced Responses for Task-based Dialogue Systems.

How are we positioning degree apprenticeships? Analysis of adverts (2021)
Presentation / Conference Contribution
Fabian, K., Taylor-Smith, E., & Smith, S. (2021). How are we positioning degree apprenticeships? Analysis of adverts. In SRHE International Conference on Research into Higher Education

Degree apprentices are recruited by employers, rather than universities, reflecting their status as paid employees, first and foremost. This study analysed job adverts for IT degree apprenticeship roles to investigate the: skills, attributes, and qua... Read More about How are we positioning degree apprenticeships? Analysis of adverts.

Underreporting of errors in NLG output, and what to do about it (2021)
Presentation / Conference Contribution
van Miltenburg, E., Clinciu, M., Dušek, O., Gkatzia, D., Inglis, S., Leppänen, L., Mahamood, S., Manning, E., Schoch, S., Thomson, C., & Wen, L. (2021, September). Underreporting of errors in NLG output, and what to do about it. Presented at 14th International Conference on Natural Language Generation, Aberdeen, UK

We observe a severe under-reporting of the different kinds of errors that Natural Language Generation systems make. This is a problem, because mistakes are an important indicator of where systems should still be improved. If authors only report overa... Read More about Underreporting of errors in NLG output, and what to do about it.

The Multimodal Turing Test for Realistic Humanoid Robots with Embodied Artificial Intelligence (2021)
Presentation / Conference Contribution
Strathearn, C., & Ma, M. (2020, July). The Multimodal Turing Test for Realistic Humanoid Robots with Embodied Artificial Intelligence. Presented at Lifelike Computing Systems: 8th Edition in the Evolution of the Series of Autonomously Learning and Optimizing Systems (SAOS), Online

Alan Turing developed the Turing Test as a method to determine whether artificial intelligence (AI) can deceive human interrogators into believing it is sentient by competently answering questions at a confidence rate of 30%+. However, the Turing Tes... Read More about The Multimodal Turing Test for Realistic Humanoid Robots with Embodied Artificial Intelligence.

Using IOTA as an Inter-Vehicular Trust Mechanism in Autonomous Vehicles (2021)
Presentation / Conference Contribution
Cutajar, O., Moradpoor, N., & Jaroucheh, Z. (2021, December). Using IOTA as an Inter-Vehicular Trust Mechanism in Autonomous Vehicles. Presented at SINCONF 2021: 14th International Conference on Security of Information and Networks, Edinburgh (Online)

In a perfect world, coordination and cooperation across distributed autonomous systems would be a trivial task. However, incomplete information, malicious actors and real-world conditions can provide challenges which bring the trust-worthiness of par... Read More about Using IOTA as an Inter-Vehicular Trust Mechanism in Autonomous Vehicles.

VNWTS: A Virtual Water Chlorination Process for Cybersecurity Analysis of Industrial Control Systems (2021)
Presentation / Conference Contribution
Robles Durazno, A., Moradpoor, N., McWhinnie, J., & Porcel-Bustamante, J. (2021, December). VNWTS: A Virtual Water Chlorination Process for Cybersecurity Analysis of Industrial Control Systems. Presented at SINCONF 2021: 14th International Conference on Security of Information and Networks, Edinburgh (Online)

The rapid development of technology during the last decades has led to the integration of the network capabilities in the devices that are essential in the operation of Industrial Control Systems (ICS). Consequently, the attack surface of these asset... Read More about VNWTS: A Virtual Water Chlorination Process for Cybersecurity Analysis of Industrial Control Systems.

An Attribute Weight Estimation Using Particle Swarm Optimization and Machine Learning Approaches for Customer Churn Prediction (2021)
Presentation / Conference Contribution
Kanwal, S., Rashid, J., Kim, J., Nisar, M. W., Hussain, A., Batool, S., & Kanwal, R. (2021, November). An Attribute Weight Estimation Using Particle Swarm Optimization and Machine Learning Approaches for Customer Churn Prediction. Presented at 2021 International Conference on Innovative Computing (ICIC), Lahore, Pakistan

One of the most challenging problems in the telecommunications industry is predicting customer churn (CCP). Decision-makers and business experts stressed that acquiring new clients is more expensive than maintaining current ones. From current churn d... Read More about An Attribute Weight Estimation Using Particle Swarm Optimization and Machine Learning Approaches for Customer Churn Prediction.

Degree Apprentices’ Lockdown Survey: Reflections on working and studying from home (2021)
Presentation / Conference Contribution
Taylor-Smith, E., & Fabian, K. (2021). Degree Apprentices’ Lockdown Survey: Reflections on working and studying from home. In SRHE International Conference on Research into Higher Education

During the first UK lockdown period, degree apprentices in two universities in Scotland were invited to complete a short qualitative survey with their reflections on starting to work and study from home. They were encouraged to complete the survey o... Read More about Degree Apprentices’ Lockdown Survey: Reflections on working and studying from home.

Transfer learning-based method for detection of COVID-19 using X-Ray Images (2021)
Presentation / Conference Contribution
Rehman, A., Tariq, Z., Jan, S. U., Aziz, S., Khan, M. U., & Chaudry, H. N. (2021, October). Transfer learning-based method for detection of COVID-19 using X-Ray Images. Presented at 2021 International Conference on Robotics and Automation in Industry (ICRAI), Rawalpindi, Pakistan

In this paper, we have performed transfer learning using different pre-trained convolutional neural networks for binary classification of X-ray images into COVID-19 disease and normal. The dataset is gathered from two open sources. Our dataset is con... Read More about Transfer learning-based method for detection of COVID-19 using X-Ray Images.

A journey that motivates: Exploring the Associate Students Transition Framework (2021)
Presentation / Conference Contribution
Meharg, D., Varey, A., & Cairncross, S. (2021). A journey that motivates: Exploring the Associate Students Transition Framework. In 2021 IEEE Frontiers in Education Conference (FIE). https://doi.org/10.1109/FIE49875.2021.9637158

This research to practice full paper presents empirical work exploring the transition experiences of transfer students into computing degrees in Scotland. Students on this journey face transitional barriers as they adapt to the change in culture, com... Read More about A journey that motivates: Exploring the Associate Students Transition Framework.

Developing Visualisations to Enhance an Insider Threat Product: A Case Study (2021)
Presentation / Conference Contribution
Graham, M., Kukla, R., Mandrychenko, O., Hart, D., & Kennedy, J. (2021, October). Developing Visualisations to Enhance an Insider Threat Product: A Case Study. Presented at 2021 IEEE Symposium on Visualization for Cyber Security (VizSec), New Orleans, USA

This paper describes the process of developing data visualisations to enhance a commercial software platform for combating insider threat, whose existing UI, while perfectly functional, was limited in its ability to allow analysts to easily spot the... Read More about Developing Visualisations to Enhance an Insider Threat Product: A Case Study.

Compounding barriers to fairness in the digital technology ecosystem (2021)
Presentation / Conference Contribution
Woolley, S. I., Collins, T., Andras, P., Gardner, A., Ortolani, M., & Pitt, J. (2021, October). Compounding barriers to fairness in the digital technology ecosystem. Presented at 2021 IEEE International Symposium on Technology and Society (ISTAS), Waterloo, ON, Canada

A growing sense of unfairness permeates our quasi-digital society. Despite drivers supporting and motivating ethical practice in the digital technology ecosystem, there are compounding barriers to fairness that, at every level, impact technology inno... Read More about Compounding barriers to fairness in the digital technology ecosystem.