318 citations · 368 across the 10 of their papers we have counts for
10 papers
Ensemble Learning based Anomaly Detection for IoT Cybersecurity via Bayesian Hyperparameters Sensitivity Analysis
Tin Lai, Farnaz Farid, Abubakar Bello +1
The Internet of Things (IoT) integrates more than billions of intelligent devices over the globe with the capability of communicating with other connected devices with little to no…
Classification and Explanation of Distributed Denial-of-Service (DDoS) Attack Detection using Machine Learning and Shapley Additive Explanation (SHAP) Methods
Yuanyuan Wei, Julian Jang-Jaccard, Amardeep Singh +2
DDoS attacks involve overwhelming a target system with a large number of requests or traffic from multiple sources, disrupting the normal traffic of a targeted server, service, or…
Reconstruction-based LSTM-Autoencoder for Anomaly-based DDoS Attack Detection over Multivariate Time-Series Data
Yuanyuan Wei, Julian Jang-Jaccard, Fariza Sabrina +3
A Distributed Denial-of-service (DDoS) attack is a malicious attempt to disrupt the regular traffic of a targeted server, service, or network by sending a flood of traffic to overw…
Generative Adversarial Networks for Malware Detection: a Survey
Aeryn Dunmore, Julian Jang-Jaccard, Fariza Sabrina +1
Since their proposal in the 2014 paper by Ian Goodfellow, there has been an explosion of research into the area of Generative Adversarial Networks. While they have been utilised in…
Improving Multilayer-Perceptron(MLP)-based Network Anomaly Detection with Birch Clustering on CICIDS-2017 Dataset
Yuhua Yin, Julian Jang-Jaccard, Fariza Sabrina +1
Machine learning algorithms have been widely used in intrusion detection systems, including Multi-layer Perceptron (MLP). In this study, we proposed a two-stage model that combines…
Explainable and Optimally Configured Artificial Neural Networks for Attack Detection in Smart Homes
Shaleeza Sohail, Zongwen Fan, Xin Gu +1
In recent years cybersecurity has become a major concern in adaptation of smart applications. Specially, in smart homes where a large number of IoT devices are used having a secure…
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…
Training a Bidirectional GAN-based One-Class Classifier for Network Intrusion Detection
Wen Xu, Julian Jang-Jaccard, Tong Liu +1
The network intrusion detection task is challenging because of the imbalanced and unlabeled nature of the dataset it operates on. Existing generative adversarial networks (GANs), a…
IGRF-RFE: A Hybrid Feature Selection Method for MLP-based Network Intrusion Detection on UNSW-NB15 Dataset
Yuhua Yin, Julian Jang-Jaccard, Wen Xu +4
The effectiveness of machine learning models is significantly affected by the size of the dataset and the quality of features as redundant and irrelevant features can radically deg…
MSD-Kmeans: A Novel Algorithm for Efficient Detection of Global and Local Outliers
Yuanyuan Wei, Julian Jang-Jaccard, Fariza Sabrina +1
Outlier detection is a technique in data mining that aims to detect unusual or unexpected records in the dataset. Existing outlier detection algorithms have different pros and cons…