22 citations · 67 across the 14 of their papers we have counts for
14 papers
Transfer Learning of Keystroke Dynamics for Cross-Device User Authentication
Nuwan Kaluarachchi, Sevvandi Kandanaarachchi, Kristen Moore +2
Keystroke dynamics (typing patterns) can be used as a behavioural biometric modality for user authentication, with applications such as fraud prevention. While the modality has bee…
Does Teaming-Up LLMs Improve Secure Code Generation? A Comprehensive Evaluation with Multi-LLMSecCodeEval
Bushra Sabir, Shigang Liu, Seung Ick Jang +6
Automatically generating source code from natural language using large language models (LLMs) is becoming common, yet security vulnerabilities persist despite advances in fine tuni…
DEFT: A new distance-based feature set for keystroke dynamics
Nuwan Kaluarachchi, Sevvandi Kandanaarachchi, Kristen Moore +1
Keystroke dynamics is a behavioural biometric utilised for user identification and authentication. We propose a new set of features based on the distance between keys on the keyboa…
Detecting Misuse of Security APIs: A Systematic Review
Zahra Mousavi, Chadni Islam, M. Ali Babar +2
Security Application Programming Interfaces (APIs) are crucial for ensuring software security. However, their misuse introduces vulnerabilities, potentially leading to severe data…
DualVAE: Controlling Colours of Generated and Real Images
Keerth Rathakumar, David Liebowitz, Christian Walder +2
Colour controlled image generation and manipulation are of interest to artists and graphic designers. Vector Quantised Variational AutoEncoders (VQ-VAEs) with autoregressive (AR) p…
Why Do Facial Deepfake Detectors Fail?
Binh Le, Shahroz Tariq, Alsharif Abuadbba +2
Recent rapid advancements in deepfake technology have allowed the creation of highly realistic fake media, such as video, image, and audio. These materials pose significant challen…
DeepTaster: Adversarial Perturbation-Based Fingerprinting to Identify Proprietary Dataset Use in Deep Neural Networks
Seonhye Park, Alsharif Abuadbba, Shuo Wang +4
Training deep neural networks (DNNs) requires large datasets and powerful computing resources, which has led some owners to restrict redistribution without permission. Watermarking…
Deception for Cyber Defence: Challenges and Opportunities
David Liebowitz, Surya Nepal, Kristen Moore +6
Deception is rapidly growing as an important tool for cyber defence, complementing existing perimeter security measures to rapidly detect breaches and data theft. One of the factor…
PublicCheck: Public Integrity Verification for Services of Run-time Deep Models
Shuo Wang, Sharif Abuadbba, Sidharth Agarwal +6
Existing integrity verification approaches for deep models are designed for private verification (i.e., assuming the service provider is honest, with white-box access to model para…
SchemaDB: Structures in Relational Datasets
Cody James Christopher, Kristen Moore, David Liebowitz
In this paper we introduce the SchemaDB data-set; a collection of relational database schemata in both sql and graph formats. Databases are not commonly shared publicly for reasons…
Modelling Direct Messaging Networks with Multiple Recipients for Cyber Deception
Kristen Moore, Cody J. Christopher, David Liebowitz +2
Cyber deception is emerging as a promising approach to defending networks and systems against attackers and data thieves. However, despite being relatively cheap to deploy, the gen…
A comprehensive solution to retrieval-based chatbot construction
Kristen Moore, Shenjun Zhong, Zhen He +4
In this paper we present the results of our experiments in training and deploying a self-supervised retrieval-based chatbot trained with contrastive learning for assisting customer…
Robust Training Using Natural Transformation
Shuo Wang, Lingjuan Lyu, Surya Nepal +3
Previous robustness approaches for deep learning models such as data augmentation techniques via data transformation or adversarial training cannot capture real-world variations th…
OCTOPUS: Overcoming Performance andPrivatization Bottlenecks in Distributed Learning
Shuo Wang, Surya Nepal, Kristen Moore +3
The diversity and quantity of data warehouses, gathering data from distributed devices such as mobile devices, can enhance the success and robustness of machine learning algorithms…