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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

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Showing 101–150 of 261 papers

TitleStatusHype
Towards Reliable Rare Category Analysis on Graphs via Individual CalibrationCode0
Machine Learning-Based Intrusion Detection: Feature Selection versus Feature Extraction—0
Host-Based Network Intrusion Detection via Feature Flattening and Two-stage Collaborative Classifier—0
Adversarial Evasion Attacks Practicality in Networks: Testing the Impact of Dynamic Learning—0
Deep PackGen: A Deep Reinforcement Learning Framework for Adversarial Network Packet Generation—0
SoK: Pragmatic Assessment of Machine Learning for Network Intrusion DetectionCode1
POET: A Self-learning Framework for PROFINET Industrial Operations Behaviour—0
FlowTransformer: A Transformer Framework for Flow-based Network Intrusion Detection SystemsCode1
Late Breaking Results: Scalable and Efficient Hyperdimensional Computing for Network Intrusion Detection—0
BS-GAT Behavior Similarity Based Graph Attention Network for Network Intrusion Detection—0
TSI-GAN: Unsupervised Time Series Anomaly Detection using Convolutional Cycle-Consistent Generative Adversarial NetworksCode1
A Novel Multi-Stage Approach for Hierarchical Intrusion DetectionCode0
Review on the Feasibility of Adversarial Evasion Attacks and Defenses for Network Intrusion Detection Systems—0
Adv-Bot: Realistic Adversarial Botnet Attacks against Network Intrusion Detection Systems—0
EdgeServe: A Streaming System for Decentralized Model Serving—0
Deep Neural Networks based Meta-Learning for Network Intrusion Detection—0
Anomaly based network intrusion detection for IoT attacks using deep learning technique—0
Towards Adversarial Realism and Robust Learning for IoT Intrusion Detection and Classification—0
Heterogeneous Domain Adaptation for IoT Intrusion Detection: A Geometric Graph Alignment Approach—0
DRL-GAN: A Hybrid Approach for Binary and Multiclass Network Intrusion Detection—0
DOC-NAD: A Hybrid Deep One-class Classifier for Network Anomaly Detection—0
Synthesis of Adversarial DDOS Attacks Using Tabular Generative Adversarial NetworksCode0
Separating Flows in Encrypted Tunnel TrafficCode0
A Dependable Hybrid Machine Learning Model for Network Intrusion Detection—0
A Hypergraph-Based Machine Learning Ensemble Network Intrusion Detection System—0
GowFed -- A novel Federated Network Intrusion Detection System—0
TAD: Transfer Learning-based Multi-Adversarial Detection of Evasion Attacks against Network Intrusion Detection Systems—0
CAN-BERT do it? Controller Area Network Intrusion Detection System based on BERT Language Model—0
DI-NIDS: Domain Invariant Network Intrusion Detection System—0
FedDef: Defense Against Gradient Leakage in Federated Learning-based Network Intrusion Detection Systems—0
Network Intrusion Detection System in a Light Bulb—0
Explanation Method for Anomaly Detection on Mixed Numerical and Categorical Spaces—0
Zero-day DDoS Attack Detection—0
A Novel Approach To Network Intrusion Detection System Using Deep Learning For Sdn: Futuristic Approach—0
Anomal-E: A Self-Supervised Network Intrusion Detection System based on Graph Neural NetworksCode1
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
An Intrusion Detection System based on Deep Belief NetworksCode1
AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly DetectionCode1
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
Representation Learning for Content-Sensitive Anomaly Detection in Industrial NetworksCode1
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
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