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

Showing 161170 of 800 papers

TitleStatusHype
Collaborative Approaches to Enhancing Smart Vehicle Cybersecurity by AI-Driven Threat Detection0
Learning in Multiple Spaces: Few-Shot Network Attack Detection with Metric-Fused Prototypical Networks0
An Anomaly Detection System Based on Generative Classifiers for Controller Area Network0
PowerRadio: Manipulate Sensor Measurementvia Power GND Radiation0
A Temporal Convolutional Network-based Approach for Network Intrusion Detection0
Flow Exporter Impact on Intelligent Intrusion Detection Systems0
Enhancing Internet of Things Security throughSelf-Supervised Graph Neural Networks0
Comprehensive Survey on Adversarial Examples in Cybersecurity: Impacts, Challenges, and Mitigation Strategies0
PyOD 2: A Python Library for Outlier Detection with LLM-powered Model Selection0
Distributed Intrusion Detection System using Semantic-based Rules for SCADA in Smart Grid0
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Benchmark Results

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