research
∙
06/27/2023
Classification and Explanation of Distributed Denial-of-Service (DDoS) Attack Detection using Machine Learning and Shapley Additive Explanation (SHAP) Methods
DDoS attacks involve overwhelming a target system with a large number of...
share
research
∙
02/16/2023
Generative Adversarial Networks for Malware Detection: a Survey
Since their proposal in the 2014 paper by Ian Goodfellow, there has been...
research
∙
08/20/2022
Improving Multilayer-Perceptron(MLP)-based Network Anomaly Detection with Birch Clustering on CICIDS-2017 Dataset
Machine learning algorithms have been widely used in intrusion detection...
research
∙
07/21/2022
A Ransomware Triage Approach using a Task Memory based on Meta-Transfer Learning Framework
Solutions for rapid prioritization of different ransomware have been rai...
research
∙
04/14/2022
LSTM-Autoencoder based Anomaly Detection for Indoor Air Quality Time Series Data
Anomaly detection for indoor air quality (IAQ) data has become an import...
research
∙
04/07/2022
Autoencoder-based Unsupervised Intrusion Detection using Multi-Scale Convolutional Recurrent Networks
The massive growth of network traffic data leads to a large volume of da...
research
∙
03/30/2022
IGRF-RFE: A Hybrid Feature Selection Method for MLP-based Network Intrusion Detection on UNSW-NB15 Dataset
The effectiveness of machine learning models is significantly affected b...
research
∙
02/02/2022
Training a Bidirectional GAN-based One-Class Classifier for Network Intrusion Detection
The network intrusion detection task is challenging because of the imbal...
research
∙
12/04/2021
A Game-Theoretic Approach for AI-based Botnet Attack Defence
The new generation of botnets leverages Artificial Intelligent (AI) tech...
research
∙
12/01/2021
A Few-Shot Meta-Learning based Siamese Neural Network using Entropy Features for Ransomware Classification
Ransomware defense solutions that can quickly detect and classify differ...
research
∙
11/27/2021
Deep Q-Learning based Reinforcement Learning Approach for Network Intrusion Detection
The rise of the new generation of cyber threats demands more sophisticat...
research
∙
10/31/2021
Intrusion Detection using Spatial-Temporal features based on Riemannian Manifold
Network traffic data is a combination of different data bytes packets un...
research
∙
10/29/2021
A Survey on Threat Situation Awareness Systems: Framework, Techniques, and Insights
Cyberspace is full of uncertainty in terms of advanced and sophisticated...
research
∙
10/26/2021
Task-Aware Meta Learning-based Siamese Neural Network for Classifying Obfuscated Malware
Malware authors apply different obfuscation techniques on the generic fe...
research
∙
07/20/2021
A Markov Game Model for AI-based Cyber Security Attack Mitigation
The new generation of cyber threats leverages advanced AI-aided methods,...
research
∙
09/04/2020
Evaluating the Security and Economic Effects of Moving Target Defense Techniques on the Cloud
Moving Target Defense (MTD) is a proactive security mechanism which chan...
research
∙
09/03/2020
Cyber Situation Awareness Monitoring and Proactive Response for Enterprises on the Cloud
The cloud model allows many enterprises able to outsource computing reso...
research
∙
10/15/2019
MSD-Kmeans: A Novel Algorithm for Efficient Detection of Global and Local Outliers
Outlier detection is a technique in data mining that aims to detect unus...
research
∙
04/03/2019
