66 citations · 94 across the 12 of their papers we have counts for
12 papers
ExpIDS: A Drift-adaptable Network Intrusion Detection System With Improved Explainability
Ayush Kumar, Kar Wai Fok, Vrizlynn L. L. Thing
Despite all the advantages associated with Network Intrusion Detection Systems (NIDSs) that utilize machine learning (ML) models, there is a significant reluctance among cyber secu…
Network Attack Traffic Detection With Hybrid Quantum-Enhanced Convolution Neural Network
Zihao Wang, Kar Wai Fok, Vrizlynn L. L. Thing
The emerging paradigm of Quantum Machine Learning (QML) combines features of quantum computing and machine learning (ML). QML enables the generation and recognition of statistical…
Privacy-Preserving Intrusion Detection using Convolutional Neural Networks
Martin Kodys, Zhongmin Dai, Vrizlynn L. L. Thing
Privacy-preserving analytics is designed to protect valuable assets. A common service provision involves the input data from the client and the model on the analyst's side. The imp…
Enhancing Network Intrusion Detection Performance using Generative Adversarial Networks
Xinxing Zhao, Kar Wai Fok, Vrizlynn L. L. Thing
Network intrusion detection systems (NIDS) play a pivotal role in safeguarding critical digital infrastructures against cyber threats. Machine learning-based detection models appli…
Privacy preserving layer partitioning for Deep Neural Network models
Kishore Rajasekar, Randolph Loh, Kar Wai Fok +1
MLaaS (Machine Learning as a Service) has become popular in the cloud computing domain, allowing users to leverage cloud resources for running private inference of ML models on the…
Exploring Emerging Trends in 5G Malicious Traffic Analysis and Incremental Learning Intrusion Detection Strategies
Zihao Wang, Kar Wai Fok, Vrizlynn L. L. Thing
The popularity of 5G networks poses a huge challenge for malicious traffic detection technology. The reason for this is that as the use of 5G technology increases, so does the risk…