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130 results

Privacy-preserving Surveillance Methods using Homomorphic Encryption

Conference Proceeding
Bowditch, W., Abramson, W., Buchanan, W. J., Pitropakis, N., & Hall, A. J. (2020)
Privacy-preserving Surveillance Methods using Homomorphic Encryption. 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

Conference Proceeding
Christou, O., Pitropakis, N., Papadopoulos, P., Mckeown, S., & Buchanan, W. J. (2020)
Phishing URL Detection Through Top-Level Domain Analysis: A Descriptive Approach. 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 ...

A Distributed Trust Framework for Privacy-Preserving Machine Learning

Conference Proceeding
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 ...

Trust-based Ecosystem to Combat Fake News

Conference Proceeding
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

Conference Proceeding
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...

Forensic Considerations for the High Efficiency Image File Format (HEIF)

Conference Proceeding
Mckeown, S., & Russell, G. (2020)
Forensic Considerations for the High Efficiency Image File Format (HEIF). https://doi.org/10.1109/CyberSecurity49315.2020.9138890
The High Efficiency File Format (HEIF) was adopted by Apple in 2017 as their favoured means of capturing images from their camera application, with Android devices such as the...

Towards Identifying Human Actions, Intent, and Severity of APT Attacks Applying Deception Techniques - An Experiment

Conference Proceeding
Chacon, J., Mckeown, S., & Macfarlane, R. (2020)
Towards Identifying Human Actions, Intent, and Severity of APT Attacks Applying Deception Techniques - An Experiment. https://doi.org/10.1109/CyberSecurity49315.2020.9138859
Attacks by Advanced Persistent Threats (APTs) have been shown to be difficult to detect using traditional signature-and anomaly-based intrusion detection approaches. Deception...

Fast Probabilistic Consensus with Weighted Votes

Conference Proceeding
Müller, S., Penzkofer, A., Ku´smierz, B., Camargo, D., & Buchanan, W. J. (in press)
Fast Probabilistic Consensus with Weighted Votes
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 ...

Automatic Generation of Adversarial Metamorphic Malware Using MAP-Elites

Conference Proceeding
Babaagba, K. O., Tan, Z., & Hart, E. (2020)
Automatic Generation of Adversarial Metamorphic Malware Using MAP-Elites. In Applications of Evolutionary Computation. EvoApplications 2020. , (117-132). https://doi.org/10.1007/978-3-030-43722-0_8
In the field of metamorphic malware detection, training a detection model with malware samples that reflect potential mutants of the malware is crucial in developing a model r...

Understanding Personal Online Risk To Individuals Via Ontology Development

Conference Proceeding
Haynes, D. (in press)
Understanding Personal Online Risk To Individuals Via Ontology Development
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...