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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 101–125 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
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