All Outputs (4095)

A hefty dose of lemons: the importance of rituals for audiences and performers at the online Edinburgh Festival Fringe 2020 (2022)
Journal Article
Piccio, B., Helgason, I., Elsden, C., & Terras, M. (2022). A hefty dose of lemons: the importance of rituals for audiences and performers at the online Edinburgh Festival Fringe 2020. International Journal of Performance Arts and Digital Media, 18(1), 154-175. https://doi.org/10.1080/14794713.2022.2036489

When the pandemic began to affect the performance world, both festival artists and producers started to adopt creative approaches to moving their work online. In the study presented here, we focus on the 2020 Edinburgh Festival Fringe, which offered... Read More about A hefty dose of lemons: the importance of rituals for audiences and performers at the online Edinburgh Festival Fringe 2020.

Comparing the Performance of Different Classifiers for Posture Detection (2022)
Presentation / Conference Contribution
Suresh Kumar, S., Dashtipour, K., Gogate, M., Ahmad, J., Assaleh, K., Arshad, K., Imran, M. A., Abbasi, Q., & Ahmad, W. (2021, October). Comparing the Performance of Different Classifiers for Posture Detection. Presented at 16th EAI International Conference, BODYNETS 2021, Online

Human Posture Classification (HPC) is used in many fields such as human computer interfacing, security surveillance, rehabilitation, remote monitoring, and so on. This paper compares the performance of different classifiers in the detection of 3 post... Read More about Comparing the Performance of Different Classifiers for Posture Detection.

Detecting Alzheimer’s Disease Using Machine Learning Methods (2022)
Presentation / Conference Contribution
Dashtipour, K., Taylor, W., Ansari, S., Zahid, A., Gogate, M., Ahmad, J., Assaleh, K., Arshad, K., Ali Imran, M., & Abbasi, Q. (2021, October). Detecting Alzheimer’s Disease Using Machine Learning Methods. Presented at 16th EAI International Conference, BODYNETS 2021, Online

As the world is experiencing population growth, the portion of the older people, aged 65 and above, is also growing at a faster rate. As a result, the dementia with Alzheimer’s disease is expected to increase rapidly in the next few years. Currently,... Read More about Detecting Alzheimer’s Disease Using Machine Learning Methods.

Blockchain-based Platform for Secure Sharing and Validation of Vaccination Certificates (2022)
Presentation / Conference Contribution
Abubakar, M., McCarron, P., Jaroucheh, Z., Al Dubai, A., & Buchanan, B. (2021, December). Blockchain-based Platform for Secure Sharing and Validation of Vaccination Certificates. Presented at 2021 14th International Conference on Security of Information and Networks (SIN), Edinburgh

The COVID-19 pandemic has recently emerged as a worldwide health emergency that necessitates coordinated international measures. To contain the virus's spread, governments and health organisations raced to develop vaccines that would lower Covid-19 m... Read More about Blockchain-based Platform for Secure Sharing and Validation of Vaccination Certificates.

PAN-DOMAIN: Privacy-preserving Sharing and Auditing of Infection Identifier Matching (2022)
Presentation / Conference Contribution
Abramson, W., Buchanan, W. J., Sayeed, S., Pitropakis, N., & Lo, O. (2021, December). PAN-DOMAIN: Privacy-preserving Sharing and Auditing of Infection Identifier Matching. Presented at 14th International Conference on Security of Information and Networks, Edinburgh [Online]

The spread of COVID-19 has highlighted the need for a robust contact tracing infrastructure that enables infected individuals to have their contacts traced, and followed up with a test. The key entities involved within a contact tracing infrastructur... Read More about PAN-DOMAIN: Privacy-preserving Sharing and Auditing of Infection Identifier Matching.

Privacy-preserving and Trusted Threat Intelligence Sharing using Distributed Ledgers (2022)
Presentation / Conference Contribution
Ali, H., Papadopoulos, P., Ahmad, J., Pit, N., Jaroucheh, Z., & Buchanan, W. J. (2021, December). Privacy-preserving and Trusted Threat Intelligence Sharing using Distributed Ledgers. Presented at IEEE SINCONF: 14th International Conference on Security of Information and Networks, Edinburgh

Threat information sharing is considered as one of the proactive defensive approaches for enhancing the overall security of trusted partners. Trusted partner organizations can provide access to past and current cybersecurity threats for reducing the... Read More about Privacy-preserving and Trusted Threat Intelligence Sharing using Distributed Ledgers.

Min-max Training: Adversarially Robust Learning Models for Network Intrusion Detection Systems (2022)
Presentation / Conference Contribution
Grierson, S., Thomson, C., Papadopoulos, P., & Buchanan, B. (2021, December). Min-max Training: Adversarially Robust Learning Models for Network Intrusion Detection Systems. Presented at 2021 14th International Conference on Security of Information and Networks (SIN), Edinburgh, United Kingdom

Intrusion detection systems are integral to the security of networked systems for detecting malicious or anomalous network traffic. As traditional approaches are becoming less effective, machine learning and deep learning-based intrusion detection sy... Read More about Min-max Training: Adversarially Robust Learning Models for Network Intrusion Detection Systems.

HDL-IDS: A Hybrid Deep Learning Architecture for Intrusion Detection in the Internet of Vehicles (2022)
Journal Article
Ullah, S., Khan, M. A., Ahmad, J., Jamal, S. S., e Huma, Z., Hassan, M. T., Pitropakis, N., Arshad, & Buchanan, W. J. (2022). HDL-IDS: A Hybrid Deep Learning Architecture for Intrusion Detection in the Internet of Vehicles. Sensors, 22(4), Article 1340. https://doi.org/10.3390/s22041340

Internet of Vehicles (IoV) is an application of the Internet of Things (IoT) network that connects smart vehicles to the internet, and vehicles with each other. With the emergence of IoV technology, customers have placed great attention on smart vehi... Read More about HDL-IDS: A Hybrid Deep Learning Architecture for Intrusion Detection in the Internet of Vehicles.

Data-inspired co-design for museum and gallery visitor experiences (2022)
Journal Article
Darzentas, D., Cameron, H., Wagner, H., Craigon, P., Bodiaj, E., Spence, J., Tennent, P., & Benford, S. (2022). Data-inspired co-design for museum and gallery visitor experiences. Artificial intelligence for engineering design, analysis and manufacturing : AI EDAM, 36, https://doi.org/10.1017/s0890060421000317

The capture and analysis of diverse data is widely recognized as being vital to the design of new products and services across the digital economy. We focus on its use to inspire the co-design of visitor experiences in museums as a distinctive case t... Read More about Data-inspired co-design for museum and gallery visitor experiences.

GLASS: Towards Secure and Decentralized eGovernance Services using IPFS (2022)
Presentation / Conference Contribution
Chrysoulas, C., Thomson, A., Pitropakis, N., Papadopoulos, P., Lo, O., Buchanan, W. J., Domalis, G., Karacapilidis, N., Tsakalidis, D., & Tsolis, D. (2021, October). GLASS: Towards Secure and Decentralized eGovernance Services using IPFS. Presented at 7th Workshop On The Security Of Industrial Control Systems & Of Cyber-Physical Systems (CyberICPS 2021). In Conjunction With ESORICS 2021, Darmstadt, Germany

The continuously advancing digitization has provided answers to the bureaucratic problems faced by eGovernance services. This innovation led them to an era of automation, broadened the attack surface and made them a popular target for cyber attacks.... Read More about GLASS: Towards Secure and Decentralized eGovernance Services using IPFS.

SSDBN: A Single-Side Dual-Branch Network with Encoder–Decoder for Building Extraction (2022)
Journal Article
Li, Y., Lu, H., Liu, Q., Zhang, Y., & Liu, X. (2022). SSDBN: A Single-Side Dual-Branch Network with Encoder–Decoder for Building Extraction. Remote Sensing, 14(3), Article 768. https://doi.org/10.3390/rs14030768

In the field of building detection research, an accurate, state-of-the-art semantic segmentation model must be constructed to classify each pixel of the image, which has an important reference value for the statistical work of a building area. Recent... Read More about SSDBN: A Single-Side Dual-Branch Network with Encoder–Decoder for Building Extraction.

A Privacy-Preserving Platform for Recording COVID-19 Vaccine Passports (2022)
Presentation / Conference Contribution
Barati, M., Buchanan, W. J., Lo, O., & Rana, O. (2021, December). A Privacy-Preserving Platform for Recording COVID-19 Vaccine Passports. Presented at 14th IEEE/ACM International Conference on Utility and Cloud Computing, Leicester

Digital vaccination passports are being proposed by various governments internationally. Trust, scalability and security are all key challenges in implementing an online vaccine passport. Initial approaches attempt to solve this problem by using cent... Read More about A Privacy-Preserving Platform for Recording COVID-19 Vaccine Passports.

Chest X-ray Classification for the Detection of COVID-19 Using Deep Learning Techniques (2022)
Journal Article
Khan, E., Rehman, M. Z. U., Ahmed, F., Alfouzan, F. A., Alzahrani, N. M., & Ahmad, J. (2022). Chest X-ray Classification for the Detection of COVID-19 Using Deep Learning Techniques. Sensors, 22(3), Article 1211. https://doi.org/10.3390/s22031211

Recent technological developments pave the path for deep learning-based techniques to be used in almost every domain of life. The precision of deep learning techniques make it possible for these to be used in the medical field for the classification... Read More about Chest X-ray Classification for the Detection of COVID-19 Using Deep Learning Techniques.

Toward a reference architecture based science gateway framework with embedded e‐learning support (2022)
Journal Article
Pierantoni, G., Kiss, T., Bolotov, A., Kagialis, D., DesLauriers, J., Ullah, A., Chen, H., Fee, D. C. Y., Dang, H., Kovacs, J., Belehaki, A., Herekakis, T., Tsagouri, I., & Gesing, S. (2023). Toward a reference architecture based science gateway framework with embedded e‐learning support. Concurrency and Computation: Practice and Experience, 35(18), Article e6872. https://doi.org/10.1002/cpe.6872

Science gateways have been widely utilized by a large number of user communities to simplify access to complex distributed computing infrastructures. While science gateways are still becoming increasingly popular and the number of user communities is... Read More about Toward a reference architecture based science gateway framework with embedded e‐learning support.

Morpho-evolution with learning using a controller archive as an inheritance mechanism (2022)
Journal Article
Le Goff, L. K., Buchanan, E., Hart, E., Eiben, A. E., Li, W., De Carlo, M., Winfield, A. F., Hale, M. F., Woolley, R., Angus, M., Timmis, J., & Tyrrell, A. M. (2023). Morpho-evolution with learning using a controller archive as an inheritance mechanism. IEEE Transactions on Cognitive and Developmental Systems, 15(2), 507-517. https://doi.org/10.1109/tcds.2022.3148543

Most work in evolutionary robotics centres on evolving a controller for a fixed body-plan. However, previous studiessuggest that simultaneously evolving both controller and body-plan could open up many interesting possibilities. However... Read More about Morpho-evolution with learning using a controller archive as an inheritance mechanism.

Semantic Segmentation and Edge Detection—Approach to Road Detection in Very High Resolution Satellite Images (2022)
Journal Article
Ghandorh, H., Boulila, W., Masood, S., Koubaa, A., Ahmed, F., & Ahmad, J. (2022). Semantic Segmentation and Edge Detection—Approach to Road Detection in Very High Resolution Satellite Images. Remote Sensing, 14(3), Article 613. https://doi.org/10.3390/rs14030613

Road detection technology plays an essential role in a variety of applications, such as urban planning, map updating, traffic monitoring and automatic vehicle navigation. Recently, there has been much development in detecting roads in high-resolution... Read More about Semantic Segmentation and Edge Detection—Approach to Road Detection in Very High Resolution Satellite Images.

A Novel Chaotic Permutation-Substitution Image Encryption Scheme Based on Logistic Map and Random Substitution (2022)
Journal Article
Arif, J., Khan, M. A., Ghaleb, B., Ahmad, J., Munir, A., Rashid, U., & Al-Dubai, A. Y. (2022). A Novel Chaotic Permutation-Substitution Image Encryption Scheme Based on Logistic Map and Random Substitution. IEEE Access, 10, 12966-12982. https://doi.org/10.1109/access.2022.3146792

Privacy is a serious concern related to sharing videos or images among people over the Internet. As a method to preserve images’ privacy, chaos-based image encryption algorithms have been used widely to fulfil such a requirement. However, these algor... Read More about A Novel Chaotic Permutation-Substitution Image Encryption Scheme Based on Logistic Map and Random Substitution.

Ransomware: Analysing the Impact on Windows Active Directory Domain Services (2022)
Journal Article
McDonald, G., Papadopoulos, P., Pitropakis, N., Ahmad, J., & Buchanan, W. J. (2022). Ransomware: Analysing the Impact on Windows Active Directory Domain Services. Sensors, 22(3), Article 953. https://doi.org/10.3390/s22030953

Ransomware has become an increasingly popular type of malware across the past decade and continues to rise in popularity due to its high profitability. Organisations and enterprises have become prime targets for ransomware as they are more likely to... Read More about Ransomware: Analysing the Impact on Windows Active Directory Domain Services.

Introduction to the Special Issue on Intelligent Models for Security and Resilience in Cyber Physical Systems (2022)
Journal Article
Liu, Q., Liu, X., Grosu, R., & Yang, C.-N. (2022). Introduction to the Special Issue on Intelligent Models for Security and Resilience in Cyber Physical Systems. Computer Modeling in Engineering and Sciences, 131(1), 23-26. https://doi.org/10.32604/cmes.2022.020646

This article has no abstract.

A Bibliometric Study and Science Mapping Research of Intelligent Decision (2022)
Journal Article
Li, B., Xu, Z., Hong, N., & Hussain, A. (2022). A Bibliometric Study and Science Mapping Research of Intelligent Decision. Cognitive Computation, 14, 989-1008. https://doi.org/10.1007/s12559-022-09993-3

Intelligent decision (ID) has received a great deal of attention and has been integrated into various fields, such as machine learning, fuzzy inference system, and natural language processing. The advanced technologies have become hot topics and have... Read More about A Bibliometric Study and Science Mapping Research of Intelligent Decision.