Privacy-preserving Surveillance Methods using Homomorphic Encryption
Bowditch, W., Abramson, W., Buchanan, W. J., Pitropakis, N., & Hall, A. J. (2020)
Privacy-preserving Surveillance Methods using Homomorphic Encryption. In ICISSP: Proceedings of the 6th International Conference on Information Systems Security and Privacy. , (240-248). https://doi.org/10.5220/0008864902400248
Data analysis and machine learning methods often involve the processing of cleartext data, and where this could breach the rights to privacy. Increasingly, we must use encrypt...
Phishing URL Detection Through Top-Level Domain Analysis: A Descriptive Approach
Christou, O., Pitropakis, N., Papadopoulos, P., Mckeown, S., & Buchanan, W. J. (2020)
Phishing URL Detection Through Top-Level Domain Analysis: A Descriptive Approach. In Proceedings of the 6th International Conference on Information Systems Security and Privacy. , (289-298). https://doi.org/10.5220/0008902202890298
Phishing is considered to be one of the most prevalent cyber-attacks because of its immense flexibility and alarmingly high success rate. Even with adequate training and high ...
Understanding Personal Online Risk To Individuals Via Ontology Development
Haynes, D. (2020)
Understanding Personal Online Risk To Individuals Via Ontology Development. In Knowledge Organization at the Interface: Proceedings of the Sixteenth International ISKO Conference, 2020, Aalborg, Denmark. , (171-180). https://doi.org/10.5771/9783956507762-171
The concept of risk is widely misunderstood because of the different contexts in which it is used. This paper describes the development of an ontology of risk as a way of bett...
PoNW: A Secure and Scalable Proof-of-Notarized-Work Based Consensus Mechanism
Abubakar, M., Jaroucheh, Z., Al-Dubai, A., & Buchanan, W. (2020)
PoNW: A Secure and Scalable Proof-of-Notarized-Work Based Consensus Mechanism. In ICVISP 2020: Proceedings of the 2020 4th International Conference on Vision, Image and Signal Processing. https://doi.org/10.1145/3448823.3448875
The original consensus algorithm-Proof of Work (PoW) has been widely utilized in the blockchain systems and is been adopted by many cryptocurrencies, such as Bitcoin and Ether...
Towards Continuous User Authentication Using Personalised Touch-Based Behaviour
Aaby, P., Giuffrida, M. V., Buchanan, W. J., & Tan, Z. (2020)
Towards Continuous User Authentication Using Personalised Touch-Based Behaviour. In 2020 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech). https://doi.org/10.1109/DASC-PICom-CBDCom-CyberSciTech49142.2020.00023
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 e...
Fast Probabilistic Consensus with Weighted Votes
Müller, S., Penzkofer, A., Ku´smierz, B., Camargo, D., & Buchanan, W. J. (2020)
Fast Probabilistic Consensus with Weighted Votes. In Proceedings of the Future Technologies Conference (FTC) 2020, Volume 2. , (360-378). https://doi.org/10.1007/978-3-030-63089-8_24
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 ...
A Distributed Trust Framework for Privacy-Preserving Machine Learning
Abramson, W., Hall, A. J., Papadopoulos, P., Pitropakis, N., & Buchanan, W. J. (2020)
A Distributed Trust Framework for Privacy-Preserving Machine Learning. In Trust, Privacy and Security in Digital Business. , (205-220). https://doi.org/10.1007/978-3-030-58986-8_14
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 ...
Improving Classification of Metamorphic Malware by Augmenting Training Data with a Diverse Set of Evolved Mutant Samples
Babaagba, K., Tan, Z., & Hart, E. (2020)
Improving Classification of Metamorphic Malware by Augmenting Training Data with a Diverse Set of Evolved Mutant Samples. https://doi.org/10.1109/CEC48606.2020.9185668
Detecting metamorphic malware provides a challenge to machine-learning models as trained models might not generalise to future mutant variants of the malware. To address this,...
Trust-based Ecosystem to Combat Fake News
Jaroucheh, Z., Alissa, M., & Buchanan, W. J. (2020)
Trust-based Ecosystem to Combat Fake News. https://doi.org/10.1109/icbc48266.2020.9169435
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 com...
Using Amazon Alexa APIs as a Source of Digital Evidence
Krueger, C., & Mckeown, S. (2020)
Using Amazon Alexa APIs as a Source of Digital Evidence. https://doi.org/10.1109/CyberSecurity49315.2020.9138849
With the release of Amazon Alexa and the first Amazon Echo device, the company revolutionised the smart home. It allowed their users to communicate with, and control, their sm...