Outputs (701)

A Transcriptomic Appreciation of Childhood Meningococcal and Polymicrobial Sepsis from a Pro-Inflammatory and Trajectorial Perspective, a Role for Vascular Endothelial Growth Factor A and B Modulation? (2023)
Journal Article
Rashid, A., Brusletto, B. S., Al-Obeidat, F., Toufiq, M., Benakatti, G., Brierley, J., Malik, Z. A., Hussain, Z., Alkhazaimi, H., Sharief, J., Kadwa, R., Sarpal, A., Chaussabel, D., Malik, R. A., Quraishi, N., Khilnani, P., Zaki, S. A., Nadeem, R., Shaikh, G., Al-Dubai, A., …Hussain, A. (2023). A Transcriptomic Appreciation of Childhood Meningococcal and Polymicrobial Sepsis from a Pro-Inflammatory and Trajectorial Perspective, a Role for Vascular Endothelial Growth Factor A and B Modulation?. Shock, 60(4), 503-516. https://doi.org/10.1097/shk.0000000000002192

This study investigated the temporal dynamics of childhood sepsis by analyzing gene expression changes associated with proinflammatory processes. Five datasets, including four meningococcal sepsis shock (MSS) datasets (two temporal and two longitudin... Read More about A Transcriptomic Appreciation of Childhood Meningococcal and Polymicrobial Sepsis from a Pro-Inflammatory and Trajectorial Perspective, a Role for Vascular Endothelial Growth Factor A and B Modulation?.

Reliable and Scalable Routing Under Hybrid SDVN Architecture: A Graph Learning Based Method (2023)
Journal Article
Li, Z., Zhao, L., Min, G., Al-Dubai, A. Y., Hawbani, A., Zomaya, A. Y., & Luo, C. (2023). Reliable and Scalable Routing Under Hybrid SDVN Architecture: A Graph Learning Based Method. IEEE Transactions on Intelligent Transportation Systems, 24(12), 14022 - 14036. https://doi.org/10.1109/tits.2023.3300082

Greedy routing efficiently achieves routing solutions for vehicular networks due to its simplicity and reliability. However, the existing greedy routing schemes have mainly considered simple routing metrics only, e.g., distance based on the local vie... Read More about Reliable and Scalable Routing Under Hybrid SDVN Architecture: A Graph Learning Based Method.

ESPP: Efficient Sector-based Charging Scheduling and Path Planning for WRSNs with Hexagonal Topology (2023)
Journal Article
Naji, A., Hawbani, A., Wang, X., Al-Gunid, H. M., Al-Dhabi, Y., Al-Dubai, A., Hussain, A., Zhao, L., & Alsamhi, S. H. (2024). ESPP: Efficient Sector-based Charging Scheduling and Path Planning for WRSNs with Hexagonal Topology. IEEE Transactions on Sustainable Computing, 9(1), 31 - 45. https://doi.org/10.1109/tsusc.2023.3296607

Wireless Power Transfer (WPT) is a promising technology that can potentially mitigate the energy provisioning problem for sensor networks. In order to efficiently replenish energy for these battery-powered devices, designing appropriate scheduling an... Read More about ESPP: Efficient Sector-based Charging Scheduling and Path Planning for WRSNs with Hexagonal Topology.

MESON: A Mobility-aware Dependent Task Offloading Scheme for Urban Vehicular Edge Computing (2023)
Journal Article
Zhao, L., Zhang, E., Wan, S., Hawbani, A., Al-Dubai, A. Y., Min, G., & Zomaya, A. Y. (2024). MESON: A Mobility-aware Dependent Task Offloading Scheme for Urban Vehicular Edge Computing. IEEE Transactions on Mobile Computing, 23(5), 4259 - 4272. https://doi.org/10.1109/tmc.2023.3289611

Vehicular Edge Computing (VEC) is the transportation version of Mobile Edge Computing (MEC) in road scenarios. One key technology of VEC is task offloading, which allows vehicles to send their computation tasks to the surrounding Roadside Units (RSUs... Read More about MESON: A Mobility-aware Dependent Task Offloading Scheme for Urban Vehicular Edge Computing.

MedOptNet: Meta-Learning Framework for Few-shot Medical Image Classification (2023)
Journal Article
Lu, L., Cui, X., Tan, Z., & Wu, Y. (2024). MedOptNet: Meta-Learning Framework for Few-shot Medical Image Classification. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 21(4), 725-736. https://doi.org/10.1109/TCBB.2023.3284846

In the medical research domain, limited data and high annotation costs have made efficient classification under few-shot conditions a popular research area. This paper proposes a meta-learning framework, termed MedOptNet, for few-shot medical image c... Read More about MedOptNet: Meta-Learning Framework for Few-shot Medical Image Classification.

Blockchain for Cybersecurity in Cyber-Physical Systems (2023)
Book
Maleh, Y., Alazab, M., & Romdhani, I. (Eds.). (2023). Blockchain for Cybersecurity in Cyber-Physical Systems. Springer. https://doi.org/10.1007/978-3-031-25506-9

This book offers the latest research results on blockchain technology and its application for cybersecurity in cyber-physical systems. It presents crucial issues in this field and provides a sample of recent advances and insights into the research pr... Read More about Blockchain for Cybersecurity in Cyber-Physical Systems.

Hamming Distributions of Popular Perceptual Hashing Techniques (2023)
Journal Article
McKeown, S., & Buchanan, W. J. (2023). Hamming Distributions of Popular Perceptual Hashing Techniques. Forensic Science International: Digital Investigation, 44(Supplement), Article 301509. https://doi.org/10.1016/j.fsidi.2023.301509

Content-based file matching has been widely deployed for decades, largely for the detection of sources of copyright infringement, extremist materials, and abusive sexual media. Perceptual hashes, such as Microsoft's PhotoDNA, are one automated mechan... Read More about Hamming Distributions of Popular Perceptual Hashing Techniques.

An omnidirectional approach to touch-based continuous authentication (2023)
Journal Article
Aaby, P., Giuffrida, M. V., Buchanan, W. J., & Tan, Z. (2023). An omnidirectional approach to touch-based continuous authentication. Computers and Security, 128, Article 103146. https://doi.org/10.1016/j.cose.2023.103146

This paper focuses on how touch interactions on smartphones can provide a continuous user authentication service through behaviour captured by a touchscreen. While efforts are made to advance touch-based behavioural authentication, researchers often... Read More about An omnidirectional approach to touch-based continuous authentication.

Preserving Differential Privacy in Deep Learning Based on Feature Relevance Region Segmentation (2023)
Journal Article
Wang, F., Xie, M., Tan, Z., Li, Q., & Wang, C. (2024). Preserving Differential Privacy in Deep Learning Based on Feature Relevance Region Segmentation. IEEE Transactions on Emerging Topics in Computing, 12(1), 307 - 315. https://doi.org/10.1109/TETC.2023.3244174

In the era of big data, deep learning techniques provide intelligent solutions for various problems in real-life scenarios. However, deep neural networks depend on large-scale datasets including sensitive data, which causes the potential risk of priv... Read More about Preserving Differential Privacy in Deep Learning Based on Feature Relevance Region Segmentation.

Improved ICS Honeypot Techniques (2023)
Presentation / Conference Contribution
McColm, D., & Macfarlane, R. (2023, June). Improved ICS Honeypot Techniques. Paper presented at International Conference on Computer Security in the Nuclear World: Security for Safety, Vienna, Austria

As work continues to advance the security posture of ICS systems across the UKNDA estate, opportunities arise to consider the deployment of deception technologies. With high-profile attacks on ICS occurring more frequently, and increasing numbers of... Read More about Improved ICS Honeypot Techniques.

Towards The Creation Of The Future Fish Farm (2023)
Journal Article
Papadopoulos, P., Buchanan, W. J., Sayeed, S., & Pitropakis, N. (2023). Towards The Creation Of The Future Fish Farm. Journal of Surveillance, Security and Safety, 4, 1-3. https://doi.org/10.20517/jsss.2022.16

Aim: A fish farm is an area where fish raise and bred for food. Fish farm environments support the care and management of seafood within a controlled environment. Over the past few decades, there has been a remarkable increase in the calorie intake o... Read More about Towards The Creation Of The Future Fish Farm.

Big Data Analytics and Intelligent Systems for Cyber Threat Intelligence (2022)
Book
Maleh, Y., Alazab, M., Tawalbeh, L., & Romdhani, I. (Eds.). (2022). Big Data Analytics and Intelligent Systems for Cyber Threat Intelligence. River Publishers

In recent years, a considerable amount of effort has been devoted to cyber-threat protection of computer systems which is one of the most critical cybersecurity tasks for single users and businesses since even a single attack can result in compromise... Read More about Big Data Analytics and Intelligent Systems for Cyber Threat Intelligence.

Using Social Media & Sentiment Analysis to Make Investment Decisions (2022)
Journal Article
Hasselgren, B., Chrysoulas, C., Pitropakis, N., & Buchanan, W. J. (2023). Using Social Media & Sentiment Analysis to Make Investment Decisions. Future Internet, 15(1), Article 5. https://doi.org/10.3390/fi15010005

Making investment decisions by utilizing sentiment data from social media (SM) is starting to become a more tangible concept. There has been a broad investigation into this field of study over the last decade, and many of the findings have promising... Read More about Using Social Media & Sentiment Analysis to Make Investment Decisions.

A framework for live host-based Bitcoin wallet forensics and triage (2022)
Journal Article
Holmes, A., & Buchanan, W. J. (2023). A framework for live host-based Bitcoin wallet forensics and triage. Forensic Science International: Digital Investigation, 44, Article 301486. https://doi.org/10.1016/j.fsidi.2022.301486

Organised crime and cybercriminals use Bitcoin, a popular cryptocurrency, to launder money and move it across borders with impunity. The UK and other countries have legislation to recover the proceeds of crime from criminals. Recent UK case law has r... Read More about A framework for live host-based Bitcoin wallet forensics and triage.

A forensic analysis of streaming platforms on Android OS (2022)
Journal Article
Murias, J. G., Levick, D., & McKeown, S. (2023). A forensic analysis of streaming platforms on Android OS. Forensic Science International: Digital Investigation, 44, Article 301485. https://doi.org/10.1016/j.fsidi.2022.301485

This work builds on existing research in streamed video reconstruction on the Android OS, which previously demonstrated that caching occurs in most cases for the Chrome and Firefox Web browsers. Prior work also outlined that streaming application cac... Read More about A forensic analysis of streaming platforms on Android OS.

Comparison of Entropy Calculation Methods for Ransomware Encrypted File Identification (2022)
Journal Article
Davies, S. R., Macfarlane, R., & Buchanan, W. J. (2022). Comparison of Entropy Calculation Methods for Ransomware Encrypted File Identification. Entropy, 24(10), Article 1503. https://doi.org/10.3390/e24101503

Ransomware is a malicious class of software that utilises encryption to implement an attack on system availability. The target’s data remains encrypted and is held captive by the attacker until a ransom demand is met. A common approach used by many c... Read More about Comparison of Entropy Calculation Methods for Ransomware Encrypted File Identification.

Trusted Threat Intelligence Sharing in Practice and Performance Benchmarking through the Hyperledger Fabric Platform (2022)
Journal Article
Ali, H., Ahmad, J., Jaroucheh, Z., Papadopoulos, P., Pitropakis, N., Lo, O., Abramson, W., & Buchanan, W. J. (2022). Trusted Threat Intelligence Sharing in Practice and Performance Benchmarking through the Hyperledger Fabric Platform. Entropy, 24(10), Article 1379. https://doi.org/10.3390/e24101379

Historically, threat information sharing has relied on manual modelling and centralised network systems, which can be inefficient, insecure, and prone to errors. Alternatively, private blockchains are now widely used to address these issues and impro... Read More about Trusted Threat Intelligence Sharing in Practice and Performance Benchmarking through the Hyperledger Fabric Platform.

Ontology-Based Linked Data to Support Decision Making within Universities (2022)
Journal Article
Ashour, G., Al-Dubai, A., Romdhani, I., & Alghazzawi, D. (2022). Ontology-Based Linked Data to Support Decision Making within Universities. Mathematics, 10(17), Article 3148. https://doi.org/10.3390/math10173148

In recent years, educational institutions worked hard to automate their work using more trending technologies that prove the success in supporting decision-making processes. Most the decisions in educational institutions rely on rating the academic r... Read More about Ontology-Based Linked Data to Support Decision Making within Universities.

Ensemble learning-based IDS for sensors telemetry data in IoT networks (2022)
Journal Article
Naz, N., Khan, M. A., Alsuhibany, S. A., Diyan, M., Tan, Z., Khan, M. A., & Ahmad, J. (2022). Ensemble learning-based IDS for sensors telemetry data in IoT networks. Mathematical Biosciences and Engineering, 19(10), 10550-10580. https://doi.org/10.3934/mbe.2022493

The Internet of Things (IoT) is a paradigm that connects a range of physical smart devices to provide ubiquitous services to individuals and automate their daily tasks. IoT devices collect data from the surrounding environment and communicate with ot... Read More about Ensemble learning-based IDS for sensors telemetry data in IoT networks.

A novel flow-vector generation approach for malicious traffic detection (2022)
Journal Article
Hou, J., Liu, F., Lu, H., Tan, Z., Zhuang, X., & Tian, Z. (2022). A novel flow-vector generation approach for malicious traffic detection. Journal of Parallel and Distributed Computing, 169, 72-86. https://doi.org/10.1016/j.jpdc.2022.06.004

Malicious traffic detection is one of the most important parts of cyber security. The approaches of using the flow as the detection object are recognized as effective. Benefiting from the development of deep learning techniques, raw traffic can be di... Read More about A novel flow-vector generation approach for malicious traffic detection.