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 451–500 of 800 papers

TitleStatusHype
A Hybrid Approach for an Interpretable and Explainable Intrusion Detection System—0
T-DFNN: An Incremental Learning Algorithm for Intrusion Detection SystemsCode1
A Dynamic Watermarking Algorithm for Finite Markov Decision Problems—0
threaTrace: Detecting and Tracing Host-based Threats in Node Level Through Provenance Graph LearningCode1
A Cyber Threat Intelligence Sharing Scheme based on Federated Learning for Network Intrusion Detection—0
Intrusion Detection: Machine Learning Baseline Calculations for Image Classification—0
A Comparative Analysis of Machine Learning Algorithms for Intrusion Detection in Edge-Enabled IoT Networks—0
Intrusion Detection using Spatial-Temporal features based on Riemannian Manifold—0
TOD: GPU-accelerated Outlier Detection via Tensor OperationsCode1
Bridging the gap to real-world for network intrusion detection systems with data-centric approachCode1
Orthogonal variance-based feature selection for intrusion detection systems—0
A Modern Analysis of Aging Machine Learning Based IoT Cybersecurity Methods—0
PWG-IDS: An Intrusion Detection Model for Solving Class Imbalance in IIoT Networks Using Generative Adversarial Networks—0
An Efficient Anomaly Detection Approach using Cube Sampling with Streaming Data—0
Automating Privilege Escalation with Deep Reinforcement Learning—0
From Zero-Shot Machine Learning to Zero-Day Attack Detection—0
Evaluating the Robustness of Time Series Anomaly and Intrusion Detection Methods against Adversarial Attacks—0
LSTM Hyper-Parameter Selection for Malware Detection: Interaction Effects and Hierarchical Selection Approach—0
A Novel Online Incremental Learning Intrusion Prevention System—0
Modern Cybersecurity Solution using Supervised Machine Learning—0
Integrating Sensing and Communication in Cellular Networks via NR Sidelink—0
Intrusion Detection using Network Traffic Profiling and Machine Learning for IoT—0
Feature Analysis for Machine Learning-based IoT Intrusion Detection—0
Feature Extraction for Machine Learning-based Intrusion Detection in IoT Networks—0
End-To-End Anomaly Detection for Identifying Malicious Cyber Behavior through NLP-Based Log Embeddings—0
Online Dictionary Learning Based Fault and Cyber Attack Detection for Power Systems—0
GGNB: Graph-Based Gaussian Naive Bayes Intrusion Detection System for CAN Bus—0
An Adaptable Deep Learning-Based Intrusion Detection System to Zero-Day Attacks—0
Learning to Detect: A Data-driven Approach for Network Intrusion Detection—0
A new semi-supervised inductive transfer learning framework: Co-Transfer—0
Jasmine: A New Active Learning Approach to Combat Cybercrime—0
Intrusion Detection In Computer Networks Using Machine Learning AlgorithmsCode0
SOME/IP Intrusion Detection using Deep Learning-based Sequential Models in Automotive Ethernet Networks—0
HTTP2vec: Embedding of HTTP Requests for Detection of Anomalous Traffic—0
Evaluating Federated Learning for Intrusion Detection in Internet of Things: Review and Challenges—0
Unveiling the potential of Graph Neural Networks for robust Intrusion DetectionCode1
Synthetic flow-based cryptomining attack generation through Generative Adversarial Networks—0
Decision-forest voting scheme for classification of rare classes in network intrusion detection—0
Deep Transfer Learning Based Intrusion Detection System for Electric Vehicular Networks—0
Reinforcement Learning for Feedback-Enabled Cyber Resilience—0
Segmented Federated Learning for Adaptive Intrusion Detection System—0
Precise Feature Selection and Case Study of Intrusion Detection in an Industrial Control System (ICS) Environment—0
Feature selection for intrusion detection systems—0
Federated Learning for Intrusion Detection in IoT Security: A Hybrid Ensemble Approach—0
DeepAuditor: Distributed Online Intrusion Detection System for IoT devices via Power Side-channel Auditing—0
Zero-shot learning approach to adaptive Cybersecurity using Explainable AI—0
Artificial Neural Network for Cybersecurity: A Comprehensive Review—0
Intrusion Detection and Localization for Networked Embedded Control Systems—0
Detecting message modification attacks on the CAN bus with Temporal Convolutional NetworksCode0
Federated Learning for Intrusion Detection System: Concepts, Challenges and Future Directions—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