All Outputs (604)

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.

Investigating Machine Learning Attacks on Financial Time Series Models (2022)
Journal Article
Gallagher, M., Pitropakis, N., Chrysoulas, C., Papadopoulos, P., Mylonas, A., & Katsikas, S. (2022). Investigating Machine Learning Attacks on Financial Time Series Models. Computers and Security, 123, https://doi.org/10.1016/j.cose.2022.102933

Machine learning and Artificial Intelligence (AI) already support human decision-making and complement professional roles, and are expected in the future to be sufficiently trusted to make autonomous decisions. To trust AI systems with such tasks, a... Read More about Investigating Machine Learning Attacks on Financial Time Series Models.

Privacy-preserving systems around security, trust and identity (2022)
Thesis
Papadopoulos, P. Privacy-preserving systems around security, trust and identity. (Thesis). Edinburgh Napier University

Data has proved to be the most valuable asset in a modern world of rapidly advancing technologies. Companies are trying to maximise their profits by getting valuable insights from collected data about people’s trends and behaviour which often can be... Read More about Privacy-preserving systems around security, trust and identity.

Generating unambiguous, natural and diverse referring expressions (2022)
Thesis
Panagiaris, N. Generating unambiguous, natural and diverse referring expressions. (Thesis). Edinburgh Napier University

Referring expression generation (REG) aims at generating natural language definite descriptions for objects within images called referring expressions (REs). Despite the substantial progress in recent years, REGmodels are still far frombeing perfect.... Read More about Generating unambiguous, natural and diverse referring expressions.

Bio-based construction materials for climate change mitigation: scalability and sustainability (2022)
Thesis
Hart, J. T. T. Bio-based construction materials for climate change mitigation: scalability and sustainability. (Thesis). Edinburgh Napier University

Construction products made from timber and other organic materials are understood to contribute to climate change mitigation by causing relatively low greenhouse gas emissions in the supply chain, whilst also storing biogenic carbon within the materi... Read More about Bio-based construction materials for climate change mitigation: scalability and sustainability.

IoT for Sustainability (2022)
Book Chapter
Davison, B. (2022). IoT for Sustainability. In R. Buyya, L. Garg, G. Fortino, & S. Misra (Eds.), New Frontiers in Cloud Computing and Internet of Things (253-286). Cham: Springer. https://doi.org/10.1007/978-3-031-05528-7_10

The Internet of Things (IoT) comprises a set of complementary technologies which offer unprecedented opportunities for interacting with the physical environment. Faced with multiple pressures on our physical wellbeing such as climate change, habitat... Read More about IoT for Sustainability.

Towards Secure Multi-Agent Deep Reinforcement Learning: Adversarial Attacks and Countermeasures (2022)
Presentation / Conference Contribution
Zheng, C., Zhen, C., Xie, H., & Yang, S. (2022, June). Towards Secure Multi-Agent Deep Reinforcement Learning: Adversarial Attacks and Countermeasures. Presented at 2022 IEEE Conference on Dependable and Secure Computing (DSC), Edinburgh, United Kingdom

Reinforcement Learning (RL) is one of the most popular methods for solving complex sequential decision-making problems. Deep RL needs careful sensing of the environment, selecting algorithms as well as hyper-parameters via soft agents, and simultaneo... Read More about Towards Secure Multi-Agent Deep Reinforcement Learning: Adversarial Attacks and Countermeasures.

Digital Twin-Enabled Intelligent DDoS Detection Mechanism For Autonomous Core Networks (2022)
Journal Article
Yigit, Y., Bal, B., Karameseoglu, A., Duong, T. Q., & Canberk, B. (2022). Digital Twin-Enabled Intelligent DDoS Detection Mechanism For Autonomous Core Networks. IEEE Communications Standards Magazine, 6(3), 38-44. https://doi.org/10.1109/MCOMSTD.0001.2100022

Existing distributed denial of service attack (DDoS) solutions cannot handle highly aggregated data rates; thus, they are unsuitable for Internet service provider (ISP) core networks. This article proposes a digital twin-enabled intelligent DDoS dete... Read More about Digital Twin-Enabled Intelligent DDoS Detection Mechanism For Autonomous Core Networks.

A Proof Of Concept On Digital Twin-Controlled WiFi Core Network Selection For In-Flight Connectivity (2022)
Journal Article
Bilen, T., Ak, E., Bal, B., & Canberk, B. (2022). A Proof Of Concept On Digital Twin-Controlled WiFi Core Network Selection For In-Flight Connectivity. IEEE Communications Standards Magazine, 6(3), 60-68. https://doi.org/10.1109/MCOMSTD.0001.2100103

The in-flight connectivity (IFC) turns to a crucial need from luxury with technological advances. The WiFi-enabled IFC (W-IFC) meets most of this need by deploying access points within the aircraft. These access points can allow Internet connectivity... Read More about A Proof Of Concept On Digital Twin-Controlled WiFi Core Network Selection For In-Flight Connectivity.

Detection of Ethanol Concentration in Liquid Using a Double-Layered Resonator Operating at 5G-mm-Wave Frequencies (2022)
Journal Article
Qureshi, S. A., Abidin, Z. Z., Majid, H. A., Ashyap, A. Y. I., & See, C. H. (2022). Detection of Ethanol Concentration in Liquid Using a Double-Layered Resonator Operating at 5G-mm-Wave Frequencies. Journal of Electronic Materials, 51, 7028-7036. https://doi.org/10.1007/s11664-022-09932-w

A new sensing technique for rapidly detecting ethanol concentration in aqueous solutions based on electromagnetic resonance is discussed. The sensor has two substrate layers and operates at 5G-mm-wave frequencies. An experimental study of the new res... Read More about Detection of Ethanol Concentration in Liquid Using a Double-Layered Resonator Operating at 5G-mm-Wave Frequencies.

A Generative Neural Network for Enhancing Android Metamorphic Malware Detection based on Behaviour Profiling (2022)
Presentation / Conference Contribution
Turnbull, L., Tan, Z., & Babaagba, K. (2022, June). A Generative Neural Network for Enhancing Android Metamorphic Malware Detection based on Behaviour Profiling. Presented at The 2022 5th IEEE Conference on Dependable and Secure Computing (IEEE DSC 2022), Edinburgh [Online]

Malicious software trends show a persistent yearly increase in volume and cost impact. More than 350,000 new malicious or unwanted programs that target various technologies were registered daily over the past year. Metamorphic malware is a specifical... Read More about A Generative Neural Network for Enhancing Android Metamorphic Malware Detection based on Behaviour Profiling.

Comprehensive review on the feasibility of developing wave energy as a renewable energy resource in Australia (2022)
Journal Article
Wimalaratna, Y. P., Hassan, A., Afrouzi, H. N., Mehranzamir, K., Ahmed, J., Siddique, B. M., & Liew, S. C. (2022). Comprehensive review on the feasibility of developing wave energy as a renewable energy resource in Australia. Cleaner Energy Systems, 3, Article 100021. https://doi.org/10.1016/j.cles.2022.100021

The facts are that increasing energy demand, depletion of fossil fuel, and greenhouse gas emissions have increased the world's interest in renewable energy. Out of all RE options, Wave Energy (WE) is the least harnessed one despite the availability o... Read More about Comprehensive review on the feasibility of developing wave energy as a renewable energy resource in Australia.

Modelling the Transmission of Coxiella burnetii within a UK Dairy Herd: Investigating the Interconnected Relationship between the Parturition Cycle and Environment Contamination (2022)
Journal Article
Patsatzis, D. G., Wheelhouse, N., & Tingas, E. (2022). Modelling the Transmission of Coxiella burnetii within a UK Dairy Herd: Investigating the Interconnected Relationship between the Parturition Cycle and Environment Contamination. Veterinary Sciences, 9(10), Article 522. https://doi.org/10.3390/vetsci9100522

Q fever infection in dairy herds is introduced through the transmission of the bacterium Coxiella burnetii, resulting in multiple detrimental effects such as reduction of lactation, abortions and chronic infection. Particularly in the UK, recent evid... Read More about Modelling the Transmission of Coxiella burnetii within a UK Dairy Herd: Investigating the Interconnected Relationship between the Parturition Cycle and Environment Contamination.

Acoustic Modelling From Raw Source and Filter Components for Dysarthric Speech Recognition (2022)
Journal Article
Yue, Z., Loweimi, E., Christensen, H., Barker, J., & Cvetkovic, Z. (2022). Acoustic Modelling From Raw Source and Filter Components for Dysarthric Speech Recognition. IEEE/ACM Transactions on Audio, Speech and Language Processing, 30, 2968-2980. https://doi.org/10.1109/taslp.2022.3205766

Acoustic modelling for automatic dysarthric speech recognition (ADSR) is a challenging task. Data deficiency is a major problem and substantial differences between typical and dysarthric speech complicate the transfer learning. In this paper, we aim... Read More about Acoustic Modelling From Raw Source and Filter Components for Dysarthric Speech Recognition.

Towards real-time privacy-preserving audio-visual speech enhancement (2022)
Presentation / Conference Contribution
Gogate, M., Dashtipour, K., & Hussain, A. (2022, September). Towards real-time privacy-preserving audio-visual speech enhancement. Presented at 2nd Symposium on Security and Privacy in Speech Communication, Incheon, Korea

Human auditory cortex in everyday noisy situations is known to exploit aural and visual cues that are contextually combined by the brain’s multi-level integration strategies to selectively suppress the background noise and focus on the target speaker... Read More about Towards real-time privacy-preserving audio-visual speech enhancement.

Effect of ambient gas on cavity formation for sphere impacts on liquids (2022)
Journal Article
Williams, H., Sprittles, J., Padrino, J. C., & Denissenko, P. (2022). Effect of ambient gas on cavity formation for sphere impacts on liquids. Physical Review Fluids, 7(9), Article 094003. https://doi.org/10.1103/physrevfluids.7.094003

Formation of a splash crown and a cavity following the impact of a sphere on a body of liquid is a classical problem. In the related problem of a droplet splashing on a flat surface, it has been established that the properties of the surrounding gas... Read More about Effect of ambient gas on cavity formation for sphere impacts on liquids.

A Lightweight Image Encryption Algorithm Based on Chaotic Map and Random Substitution (2022)
Journal Article
Alghamdi, Y., Munir, A., & Ahmad, J. (2022). A Lightweight Image Encryption Algorithm Based on Chaotic Map and Random Substitution. Entropy, 24(10), Article 1344. https://doi.org/10.3390/e24101344

Chaotic-maps-based image encryption methods have been a topic of research interest for a decade. However, most of the proposed methods suffer from slow encryption time or compromise on the security of the encryption to achieve faster encryption. This... Read More about A Lightweight Image Encryption Algorithm Based on Chaotic Map and Random Substitution.

Construction Supply Chain Management in the Fourth Industrial Revolution Era (2022)
Book
Osunsanmi, T. O., Aigbavboa, C. O., Thwala, W. D., & Oke, A. E. (2022). Construction Supply Chain Management in the Fourth Industrial Revolution Era. Bingley: Emerald. https://doi.org/10.1108/9781803821597

Providing invaluable support for construction in determining the acceptable practice and standard for regulatory bodies and managers, Construction Supply Chain Management in the Fourth Industrial Revolution Era also appeals to researchers as it expan... Read More about Construction Supply Chain Management in the Fourth Industrial Revolution Era.

An empirical evaluation of a novel domain-specific language – modelling vehicle routing problems with Athos (2022)
Journal Article
Hoffmann, B., Urquhart, N., Chalmers, K., & Guckert, M. (2022). An empirical evaluation of a novel domain-specific language – modelling vehicle routing problems with Athos. Empirical Software Engineering, 27(7), Article 180. https://doi.org/10.1007/s10664-022-10210-w

Domain-specific languages (DSLs) are a popular approach among software engineers who demand for a tailored development interface. A DSL-based approach allows to encapsulate the intricacies of the target platform in transformations that turn DSL model... Read More about An empirical evaluation of a novel domain-specific language – modelling vehicle routing problems with Athos.

Sign in Human-Sound Interaction (2022)
Book Chapter
Di Donato, B. (2022). Sign in Human-Sound Interaction. In J. L. Drever, & A. Hugill (Eds.), Aural Diversity (187-192). Routledge. https://doi.org/10.4324/9781003183624-21

This chapter explores the concept of Human–Sound Interaction (HSI) in music performance in the context of Aural Diversity. HSI focuses on human factors in experiencing sound and how this affects interaction with instruments. HSI looks at people’s div... Read More about Sign in Human-Sound Interaction.