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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 76–100 of 800 papers

TitleStatusHype
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
Show:102550
← PrevPage 4 of 32Next →
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