Outputs (167)

Towards Continuous User Authentication Using Personalised Touch-Based Behaviour (2020)
Presentation / Conference Contribution
Aaby, P., Giuffrida, M. V., Buchanan, W. J., & Tan, Z. (2020, August). Towards Continuous User Authentication Using Personalised Touch-Based Behaviour. Presented at CyberSciTech 2020, Calgary, Canada

In this paper, we present an empirical evaluation of 30 features used in touch-based continuous authentication. It is essential to identify the most significant features for each user, as behaviour is different amongst humans. Thus, a fixed feature s... Read More about Towards Continuous User Authentication Using Personalised Touch-Based Behaviour.

Fast Probabilistic Consensus with Weighted Votes (2020)
Presentation / Conference Contribution
Müller, S., Penzkofer, A., Ku´smierz, B., Camargo, D., & Buchanan, W. J. (2020, November). Fast Probabilistic Consensus with Weighted Votes. Presented at FTC 2020 - Future Technologies Conference 2020, Vancouver, Canada

The fast probabilistic consensus (FPC) is a voting consensus protocol that is robust and efficient in Byzantine infrastructure. We propose an adaption of the FPC to a setting where the voting power is proportional to the nodes reputations. We model t... Read More about Fast Probabilistic Consensus with Weighted Votes.

A Distributed Trust Framework for Privacy-Preserving Machine Learning (2020)
Presentation / Conference Contribution
Abramson, W., Hall, A. J., Papadopoulos, P., Pitropakis, N., & Buchanan, W. J. (2020, September). A Distributed Trust Framework for Privacy-Preserving Machine Learning. Presented at The 17th International Conference on Trust, Privacy and Security in Digital Business - TrustBus2020, Bratislava, Slovakia

When training a machine learning model, it is standard procedure for the researcher to have full knowledge of both the data and model. However, this engenders a lack of trust between data owners and data scientists. Data owners are justifiably reluct... Read More about A Distributed Trust Framework for Privacy-Preserving Machine Learning.

Trust-based Ecosystem to Combat Fake News (2020)
Presentation / Conference Contribution
Jaroucheh, Z., Alissa, M., & Buchanan, W. J. (2020, May). Trust-based Ecosystem to Combat Fake News. Presented at 2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), Toronto, ON, Canada

The growing spread of misinformation and dis-information has grave political, social, ethical, and privacy implications for society. Therefore, there is an ethical need to combat the flow of fake news. This paper attempts to resolves some of the aspe... Read More about Trust-based Ecosystem to Combat Fake News.

TRUSTD: Combat Fake Content using Blockchain and Collective Signature Technologies (2020)
Presentation / Conference Contribution
Jaroucheh, Z., Alissa, M., Buchanan, W. J., & Liu, X. (2020). TRUSTD: Combat Fake Content using Blockchain and Collective Signature Technologies. In 2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC 2020) (1215-1220)

The growing trend of sharing news/contents, through social media platforms and the World Wide Web has been seen to impact our perception of the truth, altering our views about politics, economics, relationships, needs and wants. This is because of th... Read More about TRUSTD: Combat Fake Content using Blockchain and Collective Signature Technologies.

5G-FOG: Freezing of Gait Identification in Multi-Class Softmax Neural Network Exploiting 5G Spectrum (2020)
Presentation / Conference Contribution
Khan, J. S., Tahir, A., Ahmad, J., Shah, S. A., Abbasi, Q. H., Russell, G., & Buchanan, W. (2020, July). 5G-FOG: Freezing of Gait Identification in Multi-Class Softmax Neural Network Exploiting 5G Spectrum. Presented at 2020 Computing Conference, London

Freezing of gait (FOG) is one of the most incapacitating and disconcerting symptom in Parkinson's disease (PD). FOG is the result of neural control disorder and motor impairments, which severely impedes forward locomotion. This paper presents the exp... Read More about 5G-FOG: Freezing of Gait Identification in Multi-Class Softmax Neural Network Exploiting 5G Spectrum.

SklCoin: Toward a Scalable Proof-of-Stake and Collective Signature Based Consensus Protocol for Strong Consistency in Blockchain (2020)
Presentation / Conference Contribution
Jaroucheh, Z., Ghaleb, B., & Buchanan, W. J. (2020). SklCoin: Toward a Scalable Proof-of-Stake and Collective Signature Based Consensus Protocol for Strong Consistency in Blockchain. . https://doi.org/10.1109/icsa-c50368.2020.00034

The proof-of-work consensus protocol suffers from two main limitations: waste of energy and offering only probabilistic guarantees about the status of the blockchain. This paper introduces SklCoin, a new Byzantine consensus protocol and its correspon... Read More about SklCoin: Toward a Scalable Proof-of-Stake and Collective Signature Based Consensus Protocol for Strong Consistency in Blockchain.

Height Prediction for Growth Hormone Deficiency Treatment Planning Using Deep Learning (2020)
Presentation / Conference Contribution
Ilyas, M., Ahmad, J., Lawson, A., Khan, J. S., Tahir, A., Adeel, A., Larijani, H., Kerrouche, A., Shaikh, M. G., Buchanan, W., & Hussain, A. (2019, July). Height Prediction for Growth Hormone Deficiency Treatment Planning Using Deep Learning. Presented at 10th International Conference, BICS 2019, Guangzhou, China

Prospective studies using longitudinal patient data can be used to help to predict responsiveness to Growth Hormone (GH) therapy and assess any suspected risks. In this paper, a novel Clinical Decision Support System (CDSS) is developed to predict gr... Read More about Height Prediction for Growth Hormone Deficiency Treatment Planning Using Deep Learning.

Machine Learning for Health and Social Care Demographics in Scotland (2019)
Presentation / Conference Contribution
Buchanan, W. J., Smales, A., Lawson, A., & Chute, C. (2019, November). Machine Learning for Health and Social Care Demographics in Scotland. Paper presented at HEALTHINFO 2019, Valencia, Spain

This paper outlines an extensive study of applying machine learning to the analysis of publicly available health and social care data within Scotland, with a focus on learning the most significant variables involved in key health care outcome factors... Read More about Machine Learning for Health and Social Care Demographics in Scotland.

Next Generation Lightweight Cryptography for Smart IoT Devices: Implementation, Challenges and Applications (2019)
Presentation / Conference Contribution
Gunathilake, N. A., Buchanan, W. J., & Asif, R. (2019). Next Generation Lightweight Cryptography for Smart IoT Devices: Implementation, Challenges and Applications. . https://doi.org/10.1109/WF-IoT.2019.8767250

High/ultra-high speed data connections are currently being developed, and by the year 2020, it is expected that the 5th generation networking (5GN) should be much smarter. It would provide great quality of service (QoS) due to low latency, less imple... Read More about Next Generation Lightweight Cryptography for Smart IoT Devices: Implementation, Challenges and Applications.