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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 76–100 of 261 papers

TitleStatusHype
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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