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 771780 of 800 papers

TitleStatusHype
Bidirectional RNN for Medical Event Detection in Electronic Health Records0
Detecting Novel Processes with CANDIES -- An Holistic Novelty Detection Technique based on Probabilistic Models0
Learning Privately from Multiparty Data0
Multi-centrality Graph Spectral Decompositions and their Application to Cyber Intrusion Detection0
More Efficient Topic Modelling Through a Noun Only Approach0
Analysis of Intelligent Classifiers and Enhancing the Detection Accuracy for Intrusion Detection System0
Detecting Clusters of Anomalies on Low-Dimensional Feature Subsets with Application to Network Traffic Flow Data0
Extreme bandits0
Anomaly Detection Framework Using Rule Extraction for Efficient Intrusion Detection0
Keystroke Patterns as Prosody in Digital Writings: A Case Study with Deceptive Reviews and Essays0
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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