SOTAVerified

Network Intrusion Detection

Network intrusion detection is the task of monitoring network traffic to and from all devices on a network in order to detect computer attacks.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 151–200 of 261 papers

TitleStatusHype
Statistical Detection of Adversarial examples in Blockchain-based Federated Forest In-vehicle Network Intrusion Detection Systems—0
Bayesian Hyperparameter Optimization for Deep Neural Network-Based Network Intrusion Detection—0
CoAP-DoS: An IoT Network Intrusion Dataset—0
LBDMIDS: LSTM Based Deep Learning Model for Intrusion Detection Systems for IoT Networks—0
On Generalisability of Machine Learning-based Network Intrusion Detection Systems—0
Ensemble Classifier Design Tuned to Dataset Characteristics for Network Intrusion Detection—0
Dependable Intrusion Detection System for IoT: A Deep Transfer Learning-based Approach—0
EPASAD: Ellipsoid decision boundary based Process-Aware Stealthy Attack Detector—0
IGRF-RFE: A Hybrid Feature Selection Method for MLP-based Network Intrusion Detection on UNSW-NB15 Dataset—0
The Cross-evaluation of Machine Learning-based Network Intrusion Detection SystemsCode0
Prepare for Trouble and Make it Double. Supervised and Unsupervised Stacking for AnomalyBased Intrusion Detection—0
NetSentry: A Deep Learning Approach to Detecting Incipient Large-scale Network Attacks—0
Training a Bidirectional GAN-based One-Class Classifier for Network Intrusion Detection—0
Unsupervised Network Intrusion Detection System for AVTP in Automotive Ethernet Networks—0
Early Detection of Network Attacks Using Deep Learning—0
One-Shot Learning on Attributed Sequences—0
An Interpretable Federated Learning-based Network Intrusion Detection Framework—0
Feature Selection-based Intrusion Detection System Using Genetic Whale Optimization Algorithm and Sample-based Classification—0
Detect & Reject for Transferability of Black-box Adversarial Attacks Against Network Intrusion Detection Systems—0
Adversarial Machine Learning In Network Intrusion Detection Domain: A Systematic Review—0
Two-stage Deep Stacked Autoencoder with Shallow Learning for Network Intrusion Detection System—0
Improving the Reliability of Network Intrusion Detection Systems through Dataset Integration—0
Deep Q-Learning based Reinforcement Learning Approach for Network Intrusion DetectionCode0
A Cyber Threat Intelligence Sharing Scheme based on Federated Learning for Network Intrusion Detection—0
PWG-IDS: An Intrusion Detection Model for Solving Class Imbalance in IIoT Networks Using Generative Adversarial Networks—0
From Zero-Shot Machine Learning to Zero-Day Attack Detection—0
Feature Analysis for Machine Learning-based IoT Intrusion Detection—0
Feature Extraction for Machine Learning-based Intrusion Detection in IoT Networks—0
A new semi-supervised inductive transfer learning framework: Co-Transfer—0
Learning to Detect: A Data-driven Approach for Network Intrusion Detection—0
Decision-forest voting scheme for classification of rare classes in network intrusion detection—0
Deep Transfer Learning Based Intrusion Detection System for Electric Vehicular Networks—0
Segmented Federated Learning for Adaptive Intrusion Detection System—0
On the Evaluation of Sequential Machine Learning for Network Intrusion Detection—0
Towards a Privacy-preserving Deep Learning-based Network Intrusion Detection in Data Distribution Services—0
Cybersecurity Anomaly Detection in Adversarial Environments—0
Launching Adversarial Attacks against Network Intrusion Detection Systems for IoT—0
Benchmarking the Benchmark -- Analysis of Synthetic NIDS Datasets—0
Evaluating Standard Feature Sets Towards Increased Generalisability and Explainability of ML-based Network Intrusion Detection—0
Supervised Feature Selection Techniques in Network Intrusion Detection: a Critical Review—0
Exploring Edge TPU for Network Intrusion Detection in IoT—0
Explaining Network Intrusion Detection System Using Explainable AI Framework—0
TANTRA: Timing-Based Adversarial Network Traffic Reshaping Attack—0
Federated Intrusion Detection for IoT with Heterogeneous Cohort Privacy—0
Intrusion detection in IoT using artificial neural networks on UNSW-15 dataset—0
Towards Network Traffic Monitoring Using Deep Transfer Learning—0
A Novel Resampling Technique for Imbalanced Dataset Optimization—0
A Comprehensive Guide to CAN IDS Data & Introduction of the ROAD Dataset—0
RNNIDS: Enhancing Network Intrusion Detection Systems through Deep Learning—0
Review: Deep Learning Methods for Cybersecurity and Intrusion Detection Systems—0
Show:102550
← PrevPage 4 of 6Next →

No leaderboard results yet.