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04/28/2023
FlowTransformer: A Transformer Framework for Flow-based Network Intrusion Detection Systems
This paper presents the FlowTransformer framework, a novel approach for ...
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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...
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10/15/2022
DI-NIDS: Domain Invariant Network Intrusion Detection System
The performance of machine learning based network intrusion detection sy...
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10/06/2022
Network Intrusion Detection System in a Light Bulb
Internet of Things (IoT) devices are progressively being utilised in a v...
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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...
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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...
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05/09/2022
On Generalisability of Machine Learning-based Network Intrusion Detection Systems
Many of the proposed machine learning (ML) based network intrusion detec...
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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...
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03/20/2022
Inspection-L: A Self-Supervised GNN-Based Money Laundering Detection System for Bitcoin
Criminals have become increasingly experienced in using cryptocurrencies...
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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...
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11/04/2021
A Cyber Threat Intelligence Sharing Scheme based on Federated Learning for Network Intrusion Detection
The uses of Machine Learning (ML) in detection of network attacks have b...
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10/17/2021
Exploring Deep Neural Networks on Edge TPU
This paper explores the performance of Google's Edge TPU on feed forward...
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09/30/2021
From Zero-Shot Machine Learning to Zero-Day Attack Detection
The standard ML methodology assumes that the test samples are derived fr...
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08/29/2021
Feature Analysis for ML-based IIoT Intrusion Detection
Industrial Internet of Things (IIoT) networks have become an increasingl...
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08/28/2021
Feature Extraction for Machine Learning-based Intrusion Detection in IoT Networks
The tremendous numbers of network security breaches that have occurred i...
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04/19/2021
Benchmarking the Benchmark – Analysis of Synthetic NIDS Datasets
Network Intrusion Detection Systems (NIDSs) are an increasingly importan...
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04/15/2021
An Explainable Machine Learning-based Network Intrusion Detection System for Enabling Generalisability in Securing IoT Networks
Machine Learning (ML)-based network intrusion detection systems bring ma...
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03/30/2021
E-GraphSAGE: A Graph Neural Network based Intrusion Detection System
This paper presents a new network intrusion detection system (NIDS) base...
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03/30/2021
Exploring Edge TPU for Network Intrusion Detection in IoT
This paper explores Google's Edge TPU for implementing a practical netwo...
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01/27/2021
Towards a Standard Feature Set of NIDS Datasets
Network Intrusion Detection Systems (NIDSs) datasets are essential tools...
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11/18/2020
NetFlow Datasets for Machine Learning-based Network Intrusion Detection Systems
Machine Learning (ML)-based Network Intrusion Detection Systems (NIDSs) ...
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11/06/2020
