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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 51–100 of 261 papers

TitleStatusHype
A Synergistic Approach In Network Intrusion Detection By Neurosymbolic AI—0
A Network Intrusions Detection System based on a Quantum Bio Inspired Algorithm—0
A Temporal Convolutional Network-based Approach for Network Intrusion Detection—0
A Transfer Learning Approach for Network Intrusion Detection—0
Attribute Learning for Network Intrusion Detection—0
A Virtual Cybersecurity Department for Securing Digital Twins in Water Distribution Systems—0
Unsupervised Network Intrusion Detection System for AVTP in Automotive Ethernet Networks—0
Bayesian Hyperparameter Optimization for Deep Neural Network-Based Network Intrusion Detection—0
An incremental hybrid adaptive network-based IDS in Software Defined Networks to detect stealth attacks—0
Benchmarking the Benchmark -- Analysis of Synthetic NIDS Datasets—0
Explanation Method for Anomaly Detection on Mixed Numerical and Categorical Spaces—0
BS-GAT Behavior Similarity Based Graph Attention Network for Network Intrusion Detection—0
Extreme bandits—0
Analyzing and Storing Network Intrusion Detection Data using Bayesian Coresets: A Preliminary Study in Offline and Streaming Settings—0
A Robust Comparison of the KDDCup99 and NSL-KDD IoT Network Intrusion Detection Datasets Through Various Machine Learning Algorithms—0
EPASAD: Ellipsoid decision boundary based Process-Aware Stealthy Attack Detector—0
A Dependable Hybrid Machine Learning Model for Network Intrusion Detection—0
An Adversarial Robustness Benchmark for Enterprise Network Intrusion Detection—0
Ensemble Classifier Design Tuned to Dataset Characteristics for Network Intrusion Detection—0
Evaluating Generative Models for Tabular Data: Novel Metrics and Benchmarking—0
A Hypergraph-Based Machine Learning Ensemble Network Intrusion Detection System—0
Detecting APT Malware Command and Control over HTTP(S) Using Contextual Summaries—0
A Novel Resampling Technique for Imbalanced Dataset Optimization—0
A Grassmannian Approach to Zero-Shot Learning for Network Intrusion Detection—0
Deep PackGen: A Deep Reinforcement Learning Framework for Adversarial Network Packet Generation—0
A Defensive Framework Against Adversarial Attacks on Machine Learning-Based Network Intrusion Detection Systems—0
Energy-based Models for Video Anomaly Detection—0
Enhancing Trustworthiness in ML-Based Network Intrusion Detection with Uncertainty Quantification—0
Explaining Network Intrusion Detection System Using Explainable AI Framework—0
A Novel Deep Learning based Model to Defend Network Intrusion Detection System against Adversarial Attacks—0
Deep Transfer Learning Based Intrusion Detection System for Electric Vehicular Networks—0
Dependable Intrusion Detection System for IoT: A Deep Transfer Learning-based Approach—0
Deep Neural Networks based Meta-Learning for Network Intrusion Detection—0
Detecting Clusters of Anomalies on Low-Dimensional Feature Subsets with Application to Network Traffic Flow Data—0
1D CNN Based Network Intrusion Detection with Normalization on Imbalanced Data—0
Detecting Unknown Attacks in IoT Environments: An Open Set Classifier for Enhanced Network Intrusion Detection—0
Detection-Rate-Emphasized Multi-objective Evolutionary Feature Selection for Network Intrusion Detection—0
Detect & Reject for Transferability of Black-box Adversarial Attacks Against Network Intrusion Detection Systems—0
Are We There Yet? Unraveling the State-of-the-Art Graph Network Intrusion Detection Systems—0
DI-NIDS: Domain Invariant Network Intrusion Detection System—0
DOC-NAD: A Hybrid Deep One-class Classifier for Network Anomaly Detection—0
Domain Knowledge Aided Explainable Artificial Intelligence for Intrusion Detection and Response—0
DRL-GAN: A Hybrid Approach for Binary and Multiclass Network Intrusion Detection—0
DualNet: Locate Then Detect Effective Payload with Deep Attention Network—0
ASNM Datasets: A Collection of Network Traffic Features for Testing of Adversarial Classifiers and Network Intrusion Detectors—0
Early Detection of Network Attacks Using Deep Learning—0
Deep Adversarial Learning in Intrusion Detection: A Data Augmentation Enhanced Framework—0
EdgeServe: A Streaming System for Decentralized Model Serving—0
A Novel Approach To Network Intrusion Detection System Using Deep Learning For Sdn: Futuristic Approach—0
Efficient Network Representation for GNN-based Intrusion Detection—0
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