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 251–300 of 800 papers

TitleStatusHype
Deep Predictive Coding Neural Network for RF Anomaly Detection in Wireless Networks—0
Attentional Heterogeneous Graph Neural Network: Application to Program Reidentification—0
AIDPS:Adaptive Intrusion Detection and Prevention System for Underwater Acoustic Sensor Networks—0
Deep Reinforcement Learning for Cyber Security—0
Assessment of the Relative Importance of different hyper-parameters of LSTM for an IDS—0
Assessing Cyclostationary Malware Detection via Feature Selection and Classification—0
An Adaptable Deep Learning-Based Intrusion Detection System to Zero-Day Attacks—0
ASNM Datasets: A Collection of Network Traffic Features for Testing of Adversarial Classifiers and Network Intrusion Detectors—0
A Simple Framework to Enhance the Adversarial Robustness of Deep Learning-based Intrusion Detection System—0
A multiagent based framework secured with layered SVM-based IDS for remote healthcare systems—0
A Deep Belief Network Based Machine Learning System for Risky Host Detection—0
A Comparative Study of AI-based Intrusion Detection Techniques in Critical Infrastructures—0
A short review on Applications of Deep learning for Cyber security—0
A Secure Healthcare 5.0 System Based on Blockchain Technology Entangled with Federated Learning Technique—0
A Modern Analysis of Aging Machine Learning Based IoT Cybersecurity Methods—0
A Scalable Hierarchical Intrusion Detection System for Internet of Vehicles—0
Artificial Neural Network for Cybersecurity: A Comprehensive Review—0
A model for multi-attack classification to improve intrusion detection performance using deep learning approaches—0
A DDoS-Aware IDS Model Based on Danger Theory and Mobile Agents—0
A Machine-Learning Phase Classification Scheme for Anomaly Detection in Signals with Periodic Characteristics—0
A Robust Comparison of the KDDCup99 and NSL-KDD IoT Network Intrusion Detection Datasets Through Various Machine Learning Algorithms—0
ADASYN-Random Forest Based Intrusion Detection Model—0
ARLIF-IDS -- Attention augmented Real-Time Isolation Forest Intrusion Detection System—0
Early Detection of Network Attacks Using Deep Learning—0
A Machine Learning Based Intrusion Detection System for Software Defined 5G Network—0
End-to-End Adversarial Learning for Intrusion Detection in Computer Networks—0
End-To-End Anomaly Detection for Identifying Malicious Cyber Behavior through NLP-Based Log Embeddings—0
Energy-based Models for Video Anomaly Detection—0
A Machine Learning based Empirical Evaluation of Cyber Threat Actors High Level Attack Patterns over Low level Attack Patterns in Attributing Attacks—0
DualNet: Locate Then Detect Effective Payload with Deep Attention Network—0
DRL-GAN: A Hybrid Approach for Binary and Multiclass Network Intrusion Detection—0
Are We There Yet? Unraveling the State-of-the-Art Graph Network Intrusion Detection Systems—0
Adaptive Security Policy Management in Cloud Environments Using Reinforcement Learning—0
DRLDO: A novel DRL based De-ObfuscationSystem for Defense against Metamorphic Malware—0
Domain Knowledge Aided Explainable Artificial Intelligence for Intrusion Detection and Response—0
Dynamic Temporal Positional Encodings for Early Intrusion Detection in IoT—0
A Review of Various Datasets for Machine Learning Algorithm-Based Intrusion Detection System: Advances and Challenges—0
Eclectic Rule Extraction for Explainability of Deep Neural Network based Intrusion Detection Systems—0
ECU Identification using Neural Network Classification and Hyperparameter Tuning—0
DOC-NAD: A Hybrid Deep One-class Classifier for Network Anomaly Detection—0
EdgeServe: A Streaming System for Decentralized Model Serving—0
Effective Intrusion Detection for UAV Communications using Autoencoder-based Feature Extraction and Machine Learning Approach—0
Effective Intrusion Detection in Highly Imbalanced IoT Networks with Lightweight S2CGAN-IDS—0
Distributed Intrusion Detection System using Semantic-based Rules for SCADA in Smart Grid—0
Effective Metaheuristic Based Classifiers for Multiclass Intrusion Detection—0
Effective Multi-Stage Training Model For Edge Computing Devices In Intrusion Detection—0
Effect of Balancing Data Using Synthetic Data on the Performance of Machine Learning Classifiers for Intrusion Detection in Computer Networks—0
Efficient classification using parallel and scalable compressed model and Its application on intrusion detection—0
A Review of Machine Learning based Anomaly Detection Techniques—0
A Lightweight Multi-Attack CAN Intrusion Detection System on Hybrid FPGAs—0
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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