Outputs (92)

Investigating anti-evasion malware triggers using automated sandbox reconfiguration techniques (2020)
Journal Article
Mills, A., & Legg, P. (2021). Investigating anti-evasion malware triggers using automated sandbox reconfiguration techniques. Journal of Cybersecurity and Privacy, 1(1), 19-39. https://doi.org/10.3390/jcp1010003

Malware analysis is fundamental for defending against prevalent cyber security threats and requires a means to deploy and study behavioural software traits as more sophisticated malware is developed. Traditionally, virtual machines are used to provid... Read More about Investigating anti-evasion malware triggers using automated sandbox reconfiguration techniques.

Deep learning vs. traditional solutions for group trajectory outliers (2020)
Journal Article
Belhadi, A., Djenouri, Y., Djenouri, D., Michalak, T., & Chun-Wei Lin, J. (2022). Deep learning vs. traditional solutions for group trajectory outliers. IEEE Transactions on Cybernetics, 52(6), 4508-4519. https://doi.org/10.1109/TCYB.2020.3029338

This article introduces a new model to identify a group of trajectory outliers from a large trajectory database and proposes several algorithms. These can be split into three categories: 1) algorithms based on data mining and knowledge discovery, whi... Read More about Deep learning vs. traditional solutions for group trajectory outliers.

Harnessing adaptive novelty for automated generation of cancer treatments (2020)
Journal Article
Balaz, I., Petrić, T., Kovacevic, M., Tsompanas, M. A., & Stillman, N. (2021). Harnessing adaptive novelty for automated generation of cancer treatments. BioSystems, 199, Article 104290. https://doi.org/10.1016/j.biosystems.2020.104290

© 2020 The Authors Nanoparticles have the potential to modulate both the pharmacokinetic and pharmacodynamic profiles of drugs, thereby enhancing their therapeutic effect. The versatility of nanoparticles allows for a wide range of customization poss... Read More about Harnessing adaptive novelty for automated generation of cancer treatments.

When the decomposition meets the constraint satisfaction problem (2020)
Journal Article
Djenouri, Y., Djenouri, D., Habbas, Z., Lin, J. C., Michalak, T. P., & Cano, A. (2020). When the decomposition meets the constraint satisfaction problem. IEEE Access, 8, 207034-207043. https://doi.org/10.1109/access.2020.3038228

This paper explores the joint use of decomposition methods and parallel computing for solving constraint satisfaction problems and introduces a framework called Parallel Decomposition for Constraint Satisfaction Problems (PD-CSP). The main idea is th... Read More about When the decomposition meets the constraint satisfaction problem.

Christian engagement with the UN Sustainable Development Goals (2020)
Presentation / Conference
Brooks, I. (2020, November). Christian engagement with the UN Sustainable Development Goals. Presented at Christian Rural and Environmental Studies, Online

Conference report on research into the state of Christian engagement with the United Nations Sustainable Development Goals (SDGs) (Focus on the UK). Reports on interviews with stakeholders and quantitative research using page counts on church web do... Read More about Christian engagement with the UN Sustainable Development Goals.

Towards the identification of antibiotic-resistant bacteria causing urinary tract infections using volatile organic compounds analysis—a pilot study (2020)
Journal Article
Hewett, K., Drabinska, N., White, P., Avison, M., Persad, R., Ratcliffe, N., & de Lacy Costello, B. (2020). Towards the identification of antibiotic-resistant bacteria causing urinary tract infections using volatile organic compounds analysis—a pilot study. Antibiotics, 9(11), 797. https://doi.org/10.3390/antibiotics9110797

Antibiotic resistance is an unprecedented threat to modern medicine. The analysis of volatile organic compounds (VOCs) from bacteria potentially offers a rapid way to determine antibiotic susceptibility in bacteria. This study aimed to find the optim... Read More about Towards the identification of antibiotic-resistant bacteria causing urinary tract infections using volatile organic compounds analysis—a pilot study.

Heatmaps for visual explainability of CNN-based predictions for multivariate time series with application to healthcare (2020)
Conference Proceeding
Viton, F., Elbattah, M., Guerin, J. L., & Dequen, G. (2020). Heatmaps for visual explainability of CNN-based predictions for multivariate time series with application to healthcare. In 2020 IEEE International Conference on Healthcare Informatics (ICHI)https://doi.org/10.1109/ICHI48887.2020.9374393

The need for explainable AI is becoming increasingly important for critical decision domains such as healthcare for example. In this context, this paper is concerned with explaining the predictions of Convolutional Neural Networks (CNNs) with particu... Read More about Heatmaps for visual explainability of CNN-based predictions for multivariate time series with application to healthcare.

Assessing a decision support tool for SOC analysts (2020)
Journal Article
Happa, J., Helmhout, M., Philips, R., Thomas Bashford-Rogers, N. L., Goldsmith, M., Creese, S., …Goldsmith, M. (in press). Assessing a decision support tool for SOC analysts. Digital Threats: Research and Practice, 9(4),

It is difficult to discern real-world consequences of attacks on an enterprise when investigating network-centric data alone. In recent years, many tools have been developed to help understand attacks using visualization, but few aim to predict real-... Read More about Assessing a decision support tool for SOC analysts.

An analysis of repetition in video game music (2020)
Conference Proceeding
Hunt, S. J. (2020). An analysis of repetition in video game music.

Video game music, unlike other forms and genres of music , is comparatively young in its development, and undoubtedly heavily influenced by the hardware it was originally played on. This study observes whether the amount of repetition in video game m... Read More about An analysis of repetition in video game music.

A review of learning theories and models underpinning technology-enhanced learning artefacts (2020)
Journal Article
Hammad, R., Khan, Z., Safieddine, F., & Ahmed, A. (2020). A review of learning theories and models underpinning technology-enhanced learning artefacts. World Journal of Science, Technology and Sustainable Development, 17(4), 341-354. https://doi.org/10.1108/WJSTSD-06-2020-0062

Purpose – Various technology-enhanced learning software and tools exist where technology becomes the main driver for these developments at the expense of pedagogy. The literature reveals the missing balance between technology and pedagogy in the cont... Read More about A review of learning theories and models underpinning technology-enhanced learning artefacts.