396 citations · 1.6k across the 95 of their papers we have counts for
14 papers · 1 filter
Compression Optimality of Asymmetric Numeral Systems
Josef Pieprzyk, Jarek Duda, Marcin Pawlowski +3
Compression also known as entropy coding has a rich and long history. However, a recent explosion of multimedia Internet applications (such as teleconferencing and video streaming…
Statement-Level Vulnerability Detection: Learning Vulnerability Patterns Through Information Theory and Contrastive Learning
Van Nguyen, Trung Le, Chakkrit Tantithamthavorn +6
Software vulnerabilities are a serious and crucial concern. Typically, in a program or function consisting of hundreds or thousands of source code statements, there are only a few…
Joint User and Data Detection in Grant-Free NOMA with Attention-based BiLSTM Network
Saud Khan, Salman Durrani, Muhammad Basit Shahab +2
We consider the multi-user detection (MUD) problem in uplink grant-free non-orthogonal multiple access (NOMA), where the access point has to identify the total number and correct i…
Unraveling Threat Intelligence Through the Lens of Malicious URL Campaigns
Mahathir Almashor, Ejaz Ahmed, Benjamin Pick +6
The daily deluge of alerts is a sombre reality for Security Operations Centre (SOC) personnel worldwide. They are at the forefront of an organisation's cybersecurity infrastructure…
Transferable Graph Backdoor Attack
Shuiqiao Yang, Bao Gia Doan, Paul Montague +5
Graph Neural Networks (GNNs) have achieved tremendous success in many graph mining tasks benefitting from the message passing strategy that fuses the local structure and node featu…
Malware Triage Approach using a Task Memory based on Meta-Transfer Learning Framework
Jinting Zhu, Julian Jang-Jaccard, Ian Welch +2
To enhance the efficiency of incident response triage operations, it is not cost-effective to defend all systems equally in a complex cyber environment. Instead, prioritizing the d…
An Additive Instance-Wise Approach to Multi-class Model Interpretation
Vy Vo, Van Nguyen, Trung Le +4
Interpretable machine learning offers insights into what factors drive a certain prediction of a black-box system. A large number of interpreting methods focus on identifying expla…
LSTM-Autoencoder based Anomaly Detection for Indoor Air Quality Time Series Data
Yuanyuan Wei, Julian Jang-Jaccard, Wen Xu +3
Anomaly detection for indoor air quality (IAQ) data has become an important area of research as the quality of air is closely related to human health and well-being. However, tradi…
Towards Web Phishing Detection Limitations and Mitigation
Alsharif Abuadbba, Shuo Wang, Mahathir Almashor +4
Web phishing remains a serious cyber threat responsible for most data breaches. Machine Learning (ML)-based anti-phishing detectors are seen as an effective countermeasure, and are…
Transformer-Based Language Models for Software Vulnerability Detection
Chandra Thapa, Seung Ick Jang, Muhammad Ejaz Ahmed +3
The large transformer-based language models demonstrate excellent performance in natural language processing. By considering the transferability of the knowledge gained by these mo…
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…
Resurrecting Trust in Facial Recognition: Mitigating Backdoor Attacks in Face Recognition to Prevent Potential Privacy Breaches
Reena Zelenkova, Jack Swallow, M. A. P. Chamikara +5
Biometric data, such as face images, are often associated with sensitive information (e.g medical, financial, personal government records). Hence, a data breach in a system storing…
Local Differential Privacy for Federated Learning
M. A. P. Chamikara, Dongxi Liu, Seyit Camtepe +4
Advanced adversarial attacks such as membership inference and model memorization can make federated learning (FL) vulnerable and potentially leak sensitive private data. Local diff…
Physical Publicly Verifiable Randomness from Pulsars
J. R. Dawson, George Hobbs, Yansong Gao +8
We demonstrate how radio pulsars can be used as random number generators. Specifically, we focus on publicly verifiable randomness (PVR), in which the same sequence of trusted and…