SOTAVerified

Intrusion Detection

Intrusion Detection is the process of dynamically monitoring events occurring in a computer system or network, analyzing them for signs of possible incidents and often interdicting the unauthorized access. This is typically accomplished by automatically collecting information from a variety of systems and network sources, and then analyzing the information for possible security problems.

Source: Machine Learning Techniques for Intrusion Detection

Papers

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Showing 51–100 of 800 papers

TitleStatusHype
Edge-Detect: Edge-centric Network Intrusion Detection using Deep Neural NetworkCode1
STATGRAPH: Effective In-vehicle Intrusion Detection via Multi-view Statistical Graph LearningCode1
A flow-based IDS using Machine Learning in eBPFCode1
Intrusion Detection for Cyber-Physical Systems using Generative Adversarial Networks in Fog EnvironmentCode1
Intrusion Detection with Segmented Federated Learning for Large-Scale Multiple LANsCode1
MTH-IDS: A Multi-Tiered Hybrid Intrusion Detection System for Internet of VehiclesCode1
IoTGeM: Generalizable Models for Behaviour-Based IoT Attack DetectionCode1
Kairos: Practical Intrusion Detection and Investigation using Whole-system ProvenanceCode1
MSTREAM: Fast Anomaly Detection in Multi-Aspect StreamsCode1
PolyLUT-Add: FPGA-based LUT Inference with Wide InputsCode1
LiPar: A Lightweight Parallel Learning Model for Practical In-Vehicle Network Intrusion DetectionCode1
LogicNets: Co-Designed Neural Networks and Circuits for Extreme-Throughput ApplicationsCode1
SafeML: Safety Monitoring of Machine Learning Classifiers through Statistical Difference MeasureCode1
An Intrusion Detection System based on Deep Belief NetworksCode1
Adaptive Intrusion Detection in the Networking of Large-Scale LANs with Segmented Federated LearningCode1
A Lightweight, Efficient and Explainable-by-Design Convolutional Neural Network for Internet Traffic ClassificationCode1
ARGUS: Context-Based Detection of Stealthy IoT Infiltration AttacksCode1
A Novel SDN Dataset for Intrusion Detection in IoT NetworksCode1
Applying Self-supervised Learning to Network Intrusion Detection for Network Flows with Graph Neural NetworkCode1
On the Cross-Dataset Generalization of Machine Learning for Network Intrusion DetectionCode1
3D-IDS: Doubly Disentangled Dynamic Intrusion DetectionCode1
A Study on Transferability of Deep Learning Models for Network Intrusion DetectionCode1
Evaluating and Improving Adversarial Robustness of Machine Learning-Based Network Intrusion DetectorsCode1
Graph-based Solutions with Residuals for Intrusion Detection: the Modified E-GraphSAGE and E-ResGAT AlgorithmsCode1
CAGN-GAT Fusion: A Hybrid Contrastive Attentive Graph Neural Network for Network Intrusion DetectionCode1
Large Language Models for Cyber Security: A Systematic Literature ReviewCode0
Learning Neural Representations for Network Anomaly DetectionCode0
Kitsune: An Ensemble of Autoencoders for Online Network Intrusion DetectionCode0
A Comparative Analysis of DNN-based White-Box Explainable AI Methods in Network SecurityCode0
A Generative Model Based Honeypot for Industrial OPC UA CommunicationCode0
K-Metamodes: frequency- and ensemble-based distributed k-modes clustering for security analyticsCode0
Improving Robustness of ML Classifiers against Realizable Evasion Attacks Using Conserved FeaturesCode0
A False Sense of Security? Revisiting the State of Machine Learning-Based Industrial Intrusion DetectionCode0
Inter-Domain Fusion for Enhanced Intrusion Detection in Power Systems: An Evidence Theoretic and Meta-Heuristic ApproachCode0
Interpretable Sequence Classification via Discrete OptimizationCode0
Intrusion Detection In Computer Networks Using Machine Learning AlgorithmsCode0
Implementing Lightweight Intrusion Detection System on Resource Constrained DevicesCode0
Hybrid Isolation Forest - Application to Intrusion DetectionCode0
Fragments Expert A Graphical User Interface MATLAB Toolbox for Classification of File FragmentsCode0
eXpose: A Character-Level Convolutional Neural Network with Embeddings For Detecting Malicious URLs, File Paths and Registry KeysCode0
Gotham Dataset 2025: A Reproducible Large-Scale IoT Network Dataset for Intrusion Detection and Security ResearchCode0
Individual Packet Features are a Risk to Model Generalisation in ML-Based Intrusion DetectionCode0
Intrusion Detection Using Mouse DynamicsCode0
Evaluating Shallow and Deep Neural Networks for Network Intrusion Detection Systems in Cyber SecurityCode0
A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection in Network Traffic DataCode0
Evaluating the Performance of Machine Learning-Based Classification Models for IoT Intrusion DetectionCode0
Enhanced Convolution Neural Network with Optimized Pooling and Hyperparameter Tuning for Network Intrusion DetectionCode0
Evaluating the Potential of Quantum Machine Learning in Cybersecurity: A Case-Study on PCA-based Intrusion Detection SystemsCode0
Efficient Federated Intrusion Detection in 5G ecosystem using optimized BERT-based modelCode0
EagerNet: Early Predictions of Neural Networks for Computationally Efficient Intrusion DetectionCode0
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All datasetsCICIDS2017CIC-DDoSCIC-DoSUNSW-NB15

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Random ForestAccuracy (%)98.13—Unverified
2K-Nearest NeighborsAccuracy (%)98.07—Unverified
#ModelMetricClaimedVerifiedStatus
1MSTREAM-PCAAUC0.94—Unverified
#ModelMetricClaimedVerifiedStatus
1MSTREAM-IBAUC0.95—Unverified
#ModelMetricClaimedVerifiedStatus
1MSTREAM-AEAUC0.9—Unverified