Outputs (2072)

Green Building: An antidote to sick buliding syndrome menace in Africa (2023)
Presentation / Conference Contribution
Liphadzi, M., Osunsanmi, T., Aigbavboa, C. O., Thwala, W., Phuti, T., & Aliu, J. (2023). Green Building: An antidote to sick buliding syndrome menace in Africa. In Proceedings of the Creative Construction Conference 2023 (632-644). https://doi.org/10.331

Sick building syndrome (SBS) is the leading cause of the reduction in the building's occupancy level of satisfaction, poor indoor air quality, and other shenanigans responsible for the underperformance of building occupants and loss in property value... Read More about Green Building: An antidote to sick buliding syndrome menace in Africa.

An exploration of diversity in Embodied Music Interaction (2023)
Presentation / Conference Contribution
Di Donato, B. (2023, May). An exploration of diversity in Embodied Music Interaction. Presented at CHIME: Music Interaction and Physical Disability, University of Edinburgh, Edinburgh

This is an exploration of diversity in Embodied Music Interaction through three case studies entitled (i) Accessible interactive digital signage for the visually impaired, (ii) Human-Sound Interaction and (iii) BSL in Embodied Music Interaction (EMI)... Read More about An exploration of diversity in Embodied Music Interaction.

A Generative Adversarial Network Based Approach to Malware Generation Based on Behavioural Graphs (2023)
Presentation / Conference Contribution
McLaren, R. A., Babaagba, K., & Tan, Z. (2023). A Generative Adversarial Network Based Approach to Malware Generation Based on Behavioural Graphs. In Machine Learning, Optimization, and Data Science: 8th International Conference, LOD 2022, Certosa di Po

As the field of malware detection continues to grow, a shift in focus is occurring from feature vectors and other common, but easily obfuscated elements to a semantics based approach. This is due to the emergence of more complex malware families that... Read More about A Generative Adversarial Network Based Approach to Malware Generation Based on Behavioural Graphs.

Practical Cyber Threat Intelligence in the UK Energy Sector (2023)
Presentation / Conference Contribution
Paice, A., & McKeown, S. (2023). Practical Cyber Threat Intelligence in the UK Energy Sector. In Proceedings of the International Conference on Cybersecurity, Situational Awareness and Social Media (3-23). https://doi.org/10.1007/978-981-19-6414-5_1

The UK energy sector is a prime target for cyber-attacks by foreign states, criminals, ‘hacktivist’ groups, and terrorists. As Critical National Infrastructure (CNI), the industry needs to understand the threats it faces to mitigate risks and make ef... Read More about Practical Cyber Threat Intelligence in the UK Energy Sector.

Neutralising Adversarial Machine Learning in Industrial Control Systems Using Blockchain (2023)
Presentation / Conference Contribution
Moradpoor, N., Barati, M., Robles-Durazno, A., Abah, E., & McWhinnie, J. (2023). Neutralising Adversarial Machine Learning in Industrial Control Systems Using Blockchain. In Proceedings of the International Conference on Cybersecurity, Situational Awaren

The protection of critical national infrastructures such as drinking water, gas, and electricity is extremely important as nations are dependent on their operation and steadiness. However, despite the value of such utilities their security issues hav... Read More about Neutralising Adversarial Machine Learning in Industrial Control Systems Using Blockchain.

Deep Pre-trained Contrastive Self-Supervised Learning: A Cyberbullying Detection Approach with Augmented Datasets (2022)
Presentation / Conference Contribution
Alharigy, L. M., Al-Nuaim, H. A., & Moradpoor, N. (2022). Deep Pre-trained Contrastive Self-Supervised Learning: A Cyberbullying Detection Approach with Augmented Datasets. In 2022 14th International Conference on Computational Intelligence and Communica

Cyberbullying is a widespread problem that has only increased in recent years due to the massive dependence on social media. Although, there are many approaches for detecting cyberbullying they still need to be improved upon for more accurate detecti... Read More about Deep Pre-trained Contrastive Self-Supervised Learning: A Cyberbullying Detection Approach with Augmented Datasets.

Developing a Digital ForensicsTerminology Using Natural Language Processing (2022)
Presentation / Conference Contribution
Le Gall, M., Cole, C., Haynes, D., & Nic Daeid, N. (2022). Developing a Digital ForensicsTerminology Using Natural Language Processing. In M. Lykke, T. Svarre, D. Haynes, M. Skov, M. Thellesfsen, & D. Martinez-Avila (Eds.), Knowledge Organization across D

Post Quantum Cryptography Analysis of TLS Tunneling on a Constrained Device (2022)
Presentation / Conference Contribution
Barton, J., Pitropakis, N., Buchanan, W., Sayeed, S., & Abramson, W. (2022). Post Quantum Cryptography Analysis of TLS Tunneling on a Constrained Device. In Proceedings of the 8th International Conference on Information Systems Security and Privacy - ICI

Advances in quantum computing make Shor’s algorithm for factorising numbers ever more tractable. This threatens the security of any cryptographic system which often relies on the difficulty of factorisation. It also threatens methods based on discret... Read More about Post Quantum Cryptography Analysis of TLS Tunneling on a Constrained Device.

High Resolution Remote Sensing Water Image Segmentation Based on Dual Branch Network (2022)
Presentation / Conference Contribution
Zhang, Z., Li, Y., Liu, Q., & Liu, X. (2022). High Resolution Remote Sensing Water Image Segmentation Based on Dual Branch Network. In 2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, I

A basic stage of hydrological research is to automatically extract water body information from high-resolution remote sensing images. Various methods based on deep learning convolutional neural networks have been proposed in recent studies to achieve... Read More about High Resolution Remote Sensing Water Image Segmentation Based on Dual Branch Network.

Explainable AI and Deep Autoencoders Based Security Framework for IoT Network Attack Certainty (Extended Abstract) (2022)
Presentation / Conference Contribution
Sampath Kalutharage, C., Liu, X., & Chrysoulas, C. (2022, September). Explainable AI and Deep Autoencoders Based Security Framework for IoT Network Attack Certainty (Extended Abstract). Presented at 27th European Symposium on Research in Computer Security

Over the past few decades, Machine Learning (ML)-based intrusion detection systems (IDS) have become increasingly popular and continue to show remarkable performance in detecting attacks. However, the lack of transparency in their decision-making pro... Read More about Explainable AI and Deep Autoencoders Based Security Framework for IoT Network Attack Certainty (Extended Abstract).