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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
Diffusion-based Adversarial Purification for Intrusion DetectionCode0
PPT-GNN: A Practical Pre-Trained Spatio-Temporal Graph Neural Network for Network Security—0
Detection-Rate-Emphasized Multi-objective Evolutionary Feature Selection for Network Intrusion Detection—0
Sequential Binary Classification for Intrusion Detection—0
PolyLUT-Add: FPGA-based LUT Inference with Wide InputsCode1
Generative AI-in-the-loop: Integrating LLMs and GPTs into the Next Generation Networks—0
Strengthening Network Intrusion Detection in IoT Environments with Self-Supervised Learning and Few Shot Learning—0
A Synergistic Approach In Network Intrusion Detection By Neurosymbolic AI—0
KiNETGAN: Enabling Distributed Network Intrusion Detection through Knowledge-Infused Synthetic Data Generation—0
Practical Performance of a Distributed Processing Framework for Machine-Learning-based NIDS—0
Large Language Models in Wireless Application Design: In-Context Learning-enhanced Automatic Network Intrusion Detection—0
Large Language Models for Cyber Security: A Systematic Literature ReviewCode0
Feature Distribution Shift Mitigation with Contrastive Pretraining for Intrusion Detection—0
Integrating Graph Neural Networks with Scattering Transform for Anomaly Detection—0
An incremental hybrid adaptive network-based IDS in Software Defined Networks to detect stealth attacks—0
Dealing with Imbalanced Classes in Bot-IoT Dataset—0
EG-ConMix: An Intrusion Detection Method based on Graph Contrastive Learning—0
Problem space structural adversarial attacks for Network Intrusion Detection Systems based on Graph Neural NetworksCode1
A Dual-Tier Adaptive One-Class Classification IDS for Emerging Cyberthreats—0
Applying Self-supervised Learning to Network Intrusion Detection for Network Flows with Graph Neural NetworkCode1
An Adversarial Robustness Benchmark for Enterprise Network Intrusion Detection—0
On the Cross-Dataset Generalization of Machine Learning for Network Intrusion DetectionCode1
Machine learning-based network intrusion detection for big and imbalanced data using oversampling, stacking feature embedding and feature extraction—0
Deep Learning Applications for Intrusion Detection in Network TrafficCode0
Improving Transferability of Network Intrusion Detection in a Federated Learning SetupCode1
A Study on Transferability of Deep Learning Models for Network Intrusion DetectionCode1
Real-time Network Intrusion Detection via Decision Transformers—0
RIDE: Real-time Intrusion Detection via Explainable Machine Learning Implemented in a Memristor Hardware Architecture—0
NNG-Mix: Improving Semi-supervised Anomaly Detection with Pseudo-anomaly GenerationCode1
SecureBERT and LLAMA 2 Empowered Control Area Network Intrusion Detection and Classification—0
LiPar: A Lightweight Parallel Learning Model for Practical In-Vehicle Network Intrusion DetectionCode1
Explaining Tree Model Decisions in Natural Language for Network Intrusion Detection—0
netFound: Foundation Model for Network SecurityCode1
IoTGeM: Generalizable Models for Behaviour-Based IoT Attack DetectionCode1
The Efficacy of Transformer-based Adversarial Attacks in Security Domains—0
Give and Take: Federated Transfer Learning for Industrial IoT Network Intrusion Detection—0
ByteStack-ID: Integrated Stacked Model Leveraging Payload Byte Frequency for Grayscale Image-based Network Intrusion Detection—0
Untargeted White-box Adversarial Attack with Heuristic Defence Methods in Real-time Deep Learning based Network Intrusion Detection System—0
TII-SSRC-23 Dataset: Typological Exploration of Diverse Traffic Patterns for Intrusion Detection—0
Detecting Unknown Attacks in IoT Environments: An Open Set Classifier for Enhanced Network Intrusion Detection—0
Efficient Network Representation for GNN-based Intrusion Detection—0
Enhancing Trustworthiness in ML-Based Network Intrusion Detection with Uncertainty Quantification—0
PolyLUT: Learning Piecewise Polynomials for Ultra-Low Latency FPGA LUT-based InferenceCode1
Multidomain transformer-based deep learning for early detection of network intrusion—0
Assessing Cyclostationary Malware Detection via Feature Selection and Classification—0
Are Existing Out-Of-Distribution Techniques Suitable for Network Intrusion Detection?Code0
Performance Comparison and Implementation of Bayesian Variants for Network Intrusion Detection—0
Real-time Regular Expression Matching—0
SoK: Realistic Adversarial Attacks and Defenses for Intelligent Network Intrusion Detection—0
A Novel Deep Learning based Model to Defend Network Intrusion Detection System against Adversarial Attacks—0
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