Phishing URL Detection Through Top-Level Domain Analysis: A Descriptive Approach (2020)
Presentation / Conference Contribution
Christou, O., Pitropakis, N., Papadopoulos, P., Mckeown, S., & Buchanan, W. J. (2020, February). Phishing URL Detection Through Top-Level Domain Analysis: A Descriptive Approach. Presented at ICISSP 2020, Valletta, Malta

Phishing is considered to be one of the most prevalent cyber-attacks because of its immense flexibility and alarmingly high success rate. Even with adequate training and high situational awareness, it can still be hard for users to continually be awa... Read More about Phishing URL Detection Through Top-Level Domain Analysis: A Descriptive Approach.

Privacy-preserving Surveillance Methods using Homomorphic Encryption (2020)
Presentation / Conference Contribution
Bowditch, W., Abramson, W., Buchanan, W. J., Pitropakis, N., & Hall, A. J. (2020, February). Privacy-preserving Surveillance Methods using Homomorphic Encryption. Presented at 6th International Conference on Information Security Systems and Privacy (ICISSP), Valletta, Malta

Data analysis and machine learning methods often involve the processing of cleartext data, and where this could breach the rights to privacy. Increasingly, we must use encryption to protect all states of the data: in-transit, at-rest, and in-memory.... Read More about Privacy-preserving Surveillance Methods using Homomorphic Encryption.

Props Alive: A Framework for Augmented Reality Stop Motion Animation (2020)
Presentation / Conference Contribution
Casas, L., Kosek, M., & Mitchell, K. (2017, March). Props Alive: A Framework for Augmented Reality Stop Motion Animation. Presented at 2017 IEEE 10th Workshop on Software Engineering and Architectures for Realtime Interactive Systems (SEARIS), Los Angeles, CA, USA

Stop motion animation evolved in the early days of cinema with the aim to create an illusion of movement with static puppets posed manually each frame. Current stop motion movies introduced 3D printing processes in order to acquire animations more ac... Read More about Props Alive: A Framework for Augmented Reality Stop Motion Animation.

BCFR: Blockchain-based Controller Against False Flow Rule Injection in SDN (2020)
Presentation / Conference Contribution
Boukria, S., Guerroumi, M., & Romdhani, I. (2019, June). BCFR: Blockchain-based Controller Against False Flow Rule Injection in SDN. Presented at 11th IEEE International Workshop on Performance Evaluation of Communications in Distributed Systems and Web based Service Architectures, PEDISWESA'2019, Barcelona, Spain

Software Defined Networking (SDN) technology increases the evolution of Internet and network development. SDN, with its logical centralization of controllers and global network overview changes the network's characteristics, on term of flexibility, a... Read More about BCFR: Blockchain-based Controller Against False Flow Rule Injection in SDN.

Photo-Realistic Facial Details Synthesis from Single Image (2019)
Presentation / Conference Contribution
Chen, A., Chen, Z., Zhang, G., Zhang, Z., Mitchell, K., & Yu, J. (2019, October). Photo-Realistic Facial Details Synthesis from Single Image. Presented at 2019 IEEE/CVF International Conference on Computer Vision (ICCV), Seoul, Korea

We present a single-image 3D face synthesis technique that can handle challenging facial expressions while recovering fine geometric details. Our technique employs expression analysis for proxy face geometry generation and combines supervised and uns... Read More about Photo-Realistic Facial Details Synthesis from Single Image.

A Multi-attributes-based Trust Model of Internet of Vehicle (2019)
Presentation / Conference Contribution
Ou, W., Luo, E., Tan, Z., Xiang, L., Yi, Q., & Tian, C. (2019, December). A Multi-attributes-based Trust Model of Internet of Vehicle. Presented at 13th International Conference on Network and System Security, Sapporo, Japan

Internet of Vehicle (IoV) is an open network and it changes in constant, where there are large number of entities. Effective way to keep security of data in IoV is to establish a trustworthy mechanism. Through transmission and dissemination of trust,... Read More about A Multi-attributes-based Trust Model of Internet of Vehicle.

Machine Learning for Health and Social Care Demographics in Scotland (2019)
Presentation / Conference Contribution
Buchanan, W. J., Smales, A., Lawson, A., & Chute, C. (2019, November). Machine Learning for Health and Social Care Demographics in Scotland. Paper presented at HEALTHINFO 2019, Valencia, Spain

This paper outlines an extensive study of applying machine learning to the analysis of publicly available health and social care data within Scotland, with a focus on learning the most significant variables involved in key health care outcome factors... Read More about Machine Learning for Health and Social Care Demographics in Scotland.

WaterLeakage: A Stealthy Malware for Data Exfiltration on Industrial Control Systems Using Visual Channels (2019)
Presentation / Conference Contribution
Robles-Durazno, A., Moradpoor, N., McWhinnie, J., & Russell, G. (2019, July). WaterLeakage: A Stealthy Malware for Data Exfiltration on Industrial Control Systems Using Visual Channels. Presented at 15th IEEE International Conference on Control & Automation (ICCA), Edinburgh, Scotland

Industrial Control Systems (ICS) have faced a growing number of threats over the past few years. Reliance on isolated controls networks or air-gapped computers is no longer a feasible solution when it comes to protecting ICS. It is because the new ar... Read More about WaterLeakage: A Stealthy Malware for Data Exfiltration on Industrial Control Systems Using Visual Channels.

Wattom: Ambient Eco-feedback with Mid-air Input (2019)
Presentation / Conference Contribution
Esteves, A., Quintal, F., Caires, F., Baptista, V., & Mendes, P. (2019, June). Wattom: Ambient Eco-feedback with Mid-air Input. Presented at EX.PAT'19, University of Madeira, Funchal, Portugal

This paper presents Wattom, a highly interactive ambient eco-feedback smart plug that aims to promote a more sustainable use of electricity in the home. This paper describes our latest implementation of the Wattom plug, and three system applications.... Read More about Wattom: Ambient Eco-feedback with Mid-air Input.

A temporal-information-based adaptive routing algorithm for software defined vehicular networks (2019)
Presentation / Conference Contribution
Zhao, L., Li, Z., Li, J., Al-Dubai, A., Min, G., & Zomaya, A. Y. (2019, May). A temporal-information-based adaptive routing algorithm for software defined vehicular networks. Presented at IEEE International Conference on Communications (ICC): Ad Hoc and Sensor Networks Symposium, Shanghai, China

In Software Defined Vehicular Networks (SDVNs), most existing studies of routing consider the vehicular network as a static graph and compute the flow table based on static information. However, a static graph could only contain partial network data.... Read More about A temporal-information-based adaptive routing algorithm for software defined vehicular networks.

A novel adaptive routing and switching scheme for software-defined vehicular Networks (2019)
Presentation / Conference Contribution
Zhoa, L., Zhao, W., Gong, C., Al-Dubai, A., & Min, G. (2019, May). A novel adaptive routing and switching scheme for software-defined vehicular Networks. Presented at IEEE International Conference on Communications, Shanghai, China

Software-Defined Vehicular Networks (SDVNs) technology has been attracting significant attention as it can make Vehicular Ad Hoc Network (VANET) more efficient and intelligent. SDVN provides a flexible architecture which can decouple the network mana... Read More about A novel adaptive routing and switching scheme for software-defined vehicular Networks.

An Illumination Algorithm Approach to Solving the Micro-Depot Routing Problem (2019)
Presentation / Conference Contribution
Urquhart, N., Hoehl, S., & Hart, E. (2019, July). An Illumination Algorithm Approach to Solving the Micro-Depot Routing Problem. Presented at Genetic and Evolutionary Computation Conference (GECCO '19), Prague, Czech Republic

An increasing emphasis on reducing pollution and congestion in city centres combined with an increase in online shopping is changing the ways in which logistics companies address vehicle routing problems (VRP). We introduce the {\em micro-depot}-VRP,... Read More about An Illumination Algorithm Approach to Solving the Micro-Depot Routing Problem.

Increasing Trust in Meta-Heuristics by Using MAP-Elites (2019)
Presentation / Conference Contribution
Urquhart, N., Guckert, M., & Powers, S. (2019, July). Increasing Trust in Meta-Heuristics by Using MAP-Elites. Presented at Genetic and Evolutionary Computation COnference, Prague, Czech Republic

Intelligent AI systems using approaches containing emergent elements often encounter acceptance problems. Results do not get sufficiently explained and the procedure itself can not be fully retraced because the flow of control is dependent on stochas... Read More about Increasing Trust in Meta-Heuristics by Using MAP-Elites.

Evolving robust policies for community energy system management (2019)
Presentation / Conference Contribution
Cardoso, R., Hart, E., & Pitt, J. (2019, July). Evolving robust policies for community energy system management. Presented at GECCO '19, Prague, Czech Republic

Community energy systems (CESs) are shared energy systems in which multiple communities generate and consume energy from renewable resources. At regular time intervals, each participating community decides whether to self-supply, store, trade, or sel... Read More about Evolving robust policies for community energy system management.

Algorithm selection using deep learning without feature extraction (2019)
Presentation / Conference Contribution
Alissa, M., Sim, K., & Hart, E. (2019, July). Algorithm selection using deep learning without feature extraction. Presented at Genetic and Evolutionary Computing Conference (GECCO) 2019, Prague, Czech Republic

We propose a novel technique for algorithm-selection which adopts a deep-learning approach, specifically a Recurrent-Neural Network with Long-Short-Term-Memory (RNN-LSTM). In contrast to the majority of work in algorithm-selection, the approach does... Read More about Algorithm selection using deep learning without feature extraction.

Reviving legacy enterprise systems with microservice-based architecture within cloud environments (2019)
Presentation / Conference Contribution
Habibullah, S., Liu, X., Tan, Z., Zhang, Y., & Liu, Q. (2019, June). Reviving legacy enterprise systems with microservice-based architecture within cloud environments. Presented at 5th International Conference on Software Engineering (SOFT 2019), Copenhagen, Denmark

Evolution has always been a challenge for enterprise computing systems. The microservice based architecture is a new design model which is rapidly becoming one of the most effective means to re-architect legacy enterprise systems and to reengineer th... Read More about Reviving legacy enterprise systems with microservice-based architecture within cloud environments.

Constructing and Evaluating Visualisation Task Classifications: Process and Considerations (2019)
Presentation / Conference Contribution
Kerracher, N., & Kennedy, J. (2017, June). Constructing and Evaluating Visualisation Task Classifications: Process and Considerations. Presented at EuroVis 2017 Eurographics / IEEE VGTC Conference on Visualization 2017, Barcelona, Spain

Categorising tasks is a common pursuit in the visualisation research community, with a wide variety of taxonomies, typologies, design spaces, and frameworks having been developed over the last three decades. While these classifications are universall... Read More about Constructing and Evaluating Visualisation Task Classifications: Process and Considerations.

Identity and belonging for graduate apprenticeships in computing: the experience of first cohort degree apprentices in Scotland (2019)
Presentation / Conference Contribution
Taylor-Smith, E., Smith, S., & Smith, C. (2019, July). Identity and belonging for graduate apprenticeships in computing: the experience of first cohort degree apprentices in Scotland. Presented at Innovation and Technology in Computer Science Education (ITiCSE), Aberdeen

In September 2017, our university’s first graduate apprentices began degrees in Software Development, Cybersecurity, and Information Technology Management for Business. This study explores how apprentices experience their association with the univers... Read More about Identity and belonging for graduate apprenticeships in computing: the experience of first cohort degree apprentices in Scotland.

Simulating Dynamic Vehicle Routing Problems with Athos (2019)
Presentation / Conference Contribution
Hoffman, B., Guckert, M., Chalmers, K., & Urquhart, N. (2019, June). Simulating Dynamic Vehicle Routing Problems with Athos. Presented at ECMS2019: 33rd INTERNATIONAL ECMS CONFERENCE ON MODELLING AND SIMULATION, Napoli, Italy

Complex routing problems, such as vehicle routing problems with additional constraints, are both hard to solve and hard to express in a form that is accessible to the human expert and at the same time processible by a computer system that is supposed... Read More about Simulating Dynamic Vehicle Routing Problems with Athos.

An Agent Based Technique for Improving Multi-Stakeholder Optimisation Problems (2019)
Presentation / Conference Contribution
Urquhart, N., & Powers, S. T. (2019, June). An Agent Based Technique for Improving Multi-Stakeholder Optimisation Problems. Presented at PAAMS 2019: International Conference on Practical Applications of Agents and Multi-Agent Systems, Avila, Spain

We present an agent based framework for improving multi-stakeholder optimisation problems, which we define as optimisation problems where the solution is utilised by a number of stakeholders who have their own local preferences. We explore our ideas... Read More about An Agent Based Technique for Improving Multi-Stakeholder Optimisation Problems.