research
∙
04/28/2023
FlowTransformer: A Transformer Framework for Flow-based Network Intrusion Detection Systems
This paper presents the FlowTransformer framework, a novel approach for ...
share
research
∙
12/15/2022
DOC-NAD: A Hybrid Deep One-class Classifier for Network Anomaly Detection
Machine Learning (ML) approaches have been used to enhance the detection...
research
∙
07/19/2022
XG-BoT: An Explainable Deep Graph Neural Network for Botnet Detection and Forensics
In this paper, we proposed XG-BoT, an explainable deep graph neural netw...
research
∙
07/14/2022
Anomal-E: A Self-Supervised Network Intrusion Detection System based on Graph Neural Networks
This paper investigates Graph Neural Networks (GNNs) application for sel...
research
∙
04/08/2022
HBFL: A Hierarchical Blockchain-based Federated Learning Framework for a Collaborative IoT Intrusion Detection
The continuous strengthening of the security posture of IoT ecosystems i...
research
∙
03/20/2022
Inspection-L: A Self-Supervised GNN-Based Money Laundering Detection System for Bitcoin
Criminals have become increasingly experienced in using cryptocurrencies...
research
∙
01/19/2022
Graph Neural Network-based Android Malware Classification with Jumping Knowledge
This paper presents a new Android malware detection method based on Grap...
research
∙
03/30/2021