318 citations · 408 across the 5 of their papers we have counts for
5 papers
Relation-aware based Siamese Denoising Autoencoder for Malware Few-shot Classification
Jinting Zhu, Julian Jang-Jaccard, Ian Welch +4
When malware employs an unseen zero-day exploit, traditional security measures such as vulnerability scanners and antivirus software can fail to detect them. This is because these…
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…
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…
A Few-Shot Meta-Learning based Siamese Neural Network using Entropy Features for Ransomware Classification
Jinting Zhu, Julian Jang-Jaccard, Amardeep Singh +3
Ransomware defense solutions that can quickly detect and classify different ransomware classes to formulate rapid response plans have been in high demand in recent years. Though th…
Task-Aware Meta Learning-based Siamese Neural Network for Classifying Obfuscated Malware
Jinting Zhu, Julian Jang-Jaccard, Amardeep Singh +2
Malware authors apply different techniques of control flow obfuscation, in order to create new malware variants to avoid detection. Existing Siamese neural network (SNN)-based malw…