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 531540 of 800 papers

TitleStatusHype
Real-time Network Intrusion Detection via Decision Transformers0
Real-time Regular Expression Matching0
Real-Time Zero-Day Intrusion Detection System for Automotive Controller Area Network on FPGAs0
Reconfigurable Edge Hardware for Intelligent IDS: Systematic Approach0
Recurrent Neural Network Attention Mechanisms for Interpretable System Log Anomaly Detection0
REGARD: Rules of EngaGement for Automated cybeR Defense to aid in Intrusion Response0
Reinforcement Learning for Feedback-Enabled Cyber Resilience0
Relevant Feature Selection Model Using Data Mining for Intrusion Detection System0
RePAD: Real-time Proactive Anomaly Detection for Time Series0
ReRe: A Lightweight Real-time Ready-to-Go Anomaly Detection Approach for Time Series0
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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